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Google, Inc.","case_name_full":"","slug":"neural-ai-llc-v-google-inc","docket_number":"7:26-mc-00324","docket_number_core":"2600324","docket_number_raw":"7:26-mc-00324","docket_number_source":0,"federal_dn_office_code":"7","federal_dn_case_type":"mc","federal_dn_judge_initials_assigned":"LS","federal_dn_judge_initials_referred":"","federal_defendant_number":null,"pacer_case_id":"1172928145","cause":"Civil Miscellaneous Case","nature_of_suit":"890 Other Statutory Actions","jury_demand":"","jurisdiction_type":"Federal Question","appellate_fee_status":"","appellate_case_type_information":"","mdl_status":"","filepath_ia":"","filepath_ia_json":"","ia_upload_failure_count":null,"ia_needs_upload":true,"ia_date_first_change":"2026-08-18T16:42:54.509776-07:00","date_blocked":null,"blocked":false,"appeal_from":null,"parent_docket":null,"tags":[],"panel":[]},"parties":[],"entries":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/477140377/","id":477140377,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492727304/","id":492727304,"tags":[],"absolute_url":"","date_created":"2026-09-07T16:39:00.785485-07:00","date_modified":"2026-09-07T16:39:00.785504-07:00","sha1":"","page_count":null,"file_size":null,"filepath_local":null,"filepath_ia":"","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"","ocr_status":null,"date_upload":null,"document_number":"","attachment_number":null,"pacer_doc_id":"","is_available":false,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"","acms_document_guid":""}],"date_created":"2026-09-07T16:39:00.773401-07:00","date_modified":"2026-09-07T16:39:00.773414-07:00","date_filed":"2026-09-04","time_filed":null,"entry_number":null,"recap_sequence_number":"2026-09-04.004","pacer_sequence_number":null,"description":"Text Order MOOTING 10 Motion to Appear Pro Hac Vice entered by District Judge Leon Schydlower. A corrected motion was filed at Doc. No. 11. (This is a text-only entry generated by the court. There is no document associated with this entry.) 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Pursuant to our Administrative Policies and Procedures for Electronic Filing, the attorney hereby granted leave to practice pro hac vice in this case must register for electronic filing with our court within 10 days of this order. Registration is managed by the PACER Service Center. Entered by District Judge Leon Schydlower. (This is a text-only entry generated by the court. There is no document associated with this entry.) (LS)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/477140375/","id":477140375,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492727302/","id":492727302,"tags":[],"absolute_url":"","date_created":"2026-09-07T16:39:00.687650-07:00","date_modified":"2026-09-07T16:39:00.687666-07:00","sha1":"","page_count":null,"file_size":null,"filepath_local":null,"filepath_ia":"","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"","ocr_status":null,"date_upload":null,"document_number":"","attachment_number":null,"pacer_doc_id":"","is_available":false,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"","acms_document_guid":""}],"date_created":"2026-09-07T16:39:00.672968-07:00","date_modified":"2026-09-07T16:39:00.672989-07:00","date_filed":"2026-09-04","time_filed":null,"entry_number":null,"recap_sequence_number":"2026-09-04.002","pacer_sequence_number":null,"description":"Text Order GRANTING 9 Motion to Appear Pro Hac Vice. Pursuant to our Administrative Policies and Procedures for Electronic Filing, the attorney hereby granted leave to practice pro hac vice in this case must register for electronic filing with our court within 10 days of this order. Registration is managed by the PACER Service Center. Entered by District Judge Leon Schydlower. (This is a text-only entry generated by the court. There is no document associated with this entry.) (LS)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/477043111/","id":477043111,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492623164/","id":492623164,"tags":[],"absolute_url":"","date_created":"2026-09-04T15:05:20.581023-07:00","date_modified":"2026-09-04T15:05:20.581044-07:00","sha1":"","page_count":null,"file_size":null,"filepath_local":null,"filepath_ia":"","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"","ocr_status":null,"date_upload":null,"document_number":"","attachment_number":null,"pacer_doc_id":"","is_available":false,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Order on Motion for Miscellaneous Relief","acms_document_guid":""}],"date_created":"2026-09-04T15:05:20.565538-07:00","date_modified":"2026-09-04T15:05:20.565564-07:00","date_filed":"2026-09-04","time_filed":"16:29:23","entry_number":null,"recap_sequence_number":"2026-09-04.001","pacer_sequence_number":null,"description":"","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/477043088/","id":477043088,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492623142/","id":492623142,"tags":[],"absolute_url":"","date_created":"2026-09-04T15:05:19.545030-07:00","date_modified":"2026-09-04T15:05:19.545050-07:00","sha1":"","page_count":null,"file_size":null,"filepath_local":null,"filepath_ia":"","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"","ocr_status":null,"date_upload":null,"document_number":"","attachment_number":null,"pacer_doc_id":"","is_available":false,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Order on Motion to Appear Pro Hac Vice","acms_document_guid":""}],"date_created":"2026-09-04T15:05:19.531555-07:00","date_modified":"2026-09-04T15:05:22.599814-07:00","date_filed":"2026-09-04","time_filed":"16:27:30","entry_number":null,"recap_sequence_number":"2026-09-04.001","pacer_sequence_number":null,"description":"","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/476957322/","id":476957322,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492535198/","id":492535198,"tags":[],"absolute_url":"/docket/74667129/11/neural-ai-llc-v-google-inc/","date_created":"2026-09-04T07:06:34.322480-07:00","date_modified":"2026-09-28T03:59:30.884678-07:00","sha1":"d31b2ec87b2d8109926fc85cfa0c9b2a2a20f896","page_count":3,"file_size":229749,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.11.0.pdf","filepath_ia":"","ia_upload_failure_count":3,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-LS Document11 Filed 09/04/26 Pagelof3\n\nUNITED STATES DISTRICT COURT\nWESTERN DISTRICT OF TEXAS\nMIDLAND-ODESSA DIVISION\n\nNEURAL AI, LLC\n\nVS. Case No.: 7:26-mc-00324-LS\nGOOGLE, LLC\n\nMOTION FOR ADMISSION PRO HAC VICE\n\nTO THE HONORABLE JUDGE OF SAID COURT:\n\nComes now DayjctMe Fox , applicant herein, and\n\nmoves this Court to grant admission to the United States District Court for the Western District of\n\nGoogle LLC\n\nTexas pro hac vice to represent in this case, and\n\nwould respectfully show the Court as follows:\n\n1. Applicant is an attorney and a member of the law firm (or practices under the name of)\n\nWilson Sonsini Goodrich & Rosati with offices at:\n\nMailing address: One Market Street, Spear Tower, Suite 3300\n\nCity, State, Zip Code: San Francisco, CA 94105\n\nTelephone: 415-947-2000 racsimite: 866-974-7329\n\n2. Since January 17, 2020 , Applicant has been and presently is a\n\nmember of and in good standing with the Bar of the State of Cakroma\n\nApplicant's bar license number is 330074\n\n3. Applicant has been admitted to practice before the following courts:\nCourt: Admission date:\nNorthern District of California 9/15/2021\nNinth Circuit Court of Appeals 6/09/2020\n\nFederal Circuit Court of Appeals 12/16/2022\n\n\fCase 7:26-mc-00324-LS Document11 Filed 09/04/26 Page2of3\n\n4. Applicant is presently a member in good standing of the bars of the courts listed above,\nexcept as provided below (list any court named in the preceding paragraph before which\n\nApplicant is no longer admitted to practice):\n\n5. ] x have have not previously applied to Appear Pro Hac Vice in this district\n\ncourt in Case[s]:\n\nNumber: 9:22-cv-00031 onthe !2 day of April _ 2022\nNumber: on the day of :\nNumber: on the day of\n\n6. Applicant has never been subject to grievance proceedings or involuntary removal\n\nproceedings while a member of the bar of any state or federal court, except as\n\nprovided:\n\n7. Applicant has not been charged, arrested, or convicted of a criminal offense or offenses,\n\nexcept as provided below (omit minor traffic offenses):\n\n8. Applicant has read and is familiar with the Local Rules of the Western District of Texas\n\nand will comply with the standards of practice set out therein.\n\fCase 7:26-mc-00324-LS Document11 Filed 09/04/26 Page 3of3\n\n9. Applicant will file an Application for Admission to Practice before the United States\nDistrict Court for the Western District of Texas, if so requested; or Applicant has\nco-counsel in this case who is admitted to practice before the United States District\nCourt for the Western District of Texas.\n\n__,, Jason M. Storck\nCo-counsel:\n\nMailing address: 900 South Capital of Texas Highway, Las Cimas IV, Fifth Floor\n\nCity, State, Zip Code; Austin, TX 78746\n512-338-5400\n\nTelephone:\n\nShould the Court grant applicant's motion, Applicant shall tender the amount of $100.00 pro hac\nvice fee in compliance with Local Court Rule AT-I(f)(2) [checks made payable to: Clerk, U.S. District\n\nCourt].\n\nWherefore, Applicant prays that this Court enter an order permitting the admission of\n\nDavitt ox to the Western District of Texas pro hac vice for this case only.\n\nRespectfully submitted,\nDavid M. Fox\n\n[printed name of Applicant]\n\nLEU Ge\n\n[signature of Kpplicant]\n\nCERTIFICATE OF SERVICE\n\n[hereby certify that I have served a true and correct copy of this motion upon each attorney of\n\nrecord and the original upon the Clerk of Court on this the 4 day of September 2026 |\n\n3\n\nDavid M. Fox\n\n[printed name of Applicant]\n\nCet Se.\n\n{signature of Applicant]\n\n","ocr_status":1,"date_upload":"2026-09-07T16:40:21.534120-07:00","document_number":"11","attachment_number":null,"pacer_doc_id":"181037344251","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Miscellaneous Relief","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492727309/","id":492727309,"tags":[],"absolute_url":"/docket/74667129/11/1/neural-ai-llc-v-google-inc/","date_created":"2026-09-07T16:40:17.716155-07:00","date_modified":"2026-09-10T19:35:51.210276-07:00","sha1":"dd15cad4d71032ccac7fe4a03dd76a8738db02ed","page_count":1,"file_size":60149,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.11.1.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.11.1.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-LS Document11-1 Filed 09/04/26 Page1of1\n\nUNITED STATES DISTRICT COURT\nWESTERN DISTRICT OF TEXAS\n\nMIDLAND-ODESSA DIVISION\n\nNEURAL AI, LLC\n\nGOOGLE, LLC\n\nORDER\n\nBE IT REMEMBERED on this day, there was presented to the Court the Motion for\n\nAdmission Pro Hae Vice filed by David M. Fox , counsel for\n\nGoogle LLC\n\n, and the Court, having reviewed the motion, enters\n\nthe following order:\n\nIT IS ORDERED that the Motion for Admission Pro Hac Vice is GRANTED, and\n\nDavid M. Fox Google LLC\n\nmay appear on behalf of\n\nin the above case.\n\nIT IS FURTHER ORDERED that D@vid M. Fox if he/she\n\nhas not already done so, shall immediately tender the amount of $100.00, made payable to: Clerk, U.S.\nDistrict Court, in compliance with Local Court Rule AT-I(f)(2).\n\nSIGNED this the day of 20\n\nUNITED STATES DISTRICT JUDGE\n","ocr_status":1,"date_upload":"2026-09-07T16:49:22.641852-07:00","document_number":"11","attachment_number":1,"pacer_doc_id":"181037344252","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Proposed Order","acms_document_guid":""}],"date_created":"2026-09-04T07:06:34.292799-07:00","date_modified":"2026-09-07T16:39:00.645056-07:00","date_filed":"2026-09-04","time_filed":"09:00:26","entry_number":11,"recap_sequence_number":"2026-09-04.001","pacer_sequence_number":34,"description":"CORRECTED MOTION re 10 MOTION to Appear Pro Hac Vice by Jason M. Storck for Admission Pro Hac Vice of David Fox ( Filing fee $ 100 receipt number ATXWDC-22598138) by Google, Inc.. (Attachments: # 1 Proposed Order)(Storck, Jason) (Entered: 09/04/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/476909969/","id":476909969,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492486049/","id":492486049,"tags":[],"absolute_url":"/docket/74667129/9/neural-ai-llc-v-google-inc/","date_created":"2026-09-03T17:04:29.278466-07:00","date_modified":"2026-09-10T19:35:39.291137-07:00","sha1":"3a320ad8e967358ae04905858e2e7b0e58060d74","page_count":4,"file_size":358054,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.9.0.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.9.0.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-LS Document9 Filed 09/03/26 Page1of4\n\nUNITED STATES DISTRICT COURT\nWESTERN DISTRICT OF TEXAS\nMIDLAND-ODESSA DIVISION\n\nNEURAL AI, LLC\n\nGOOGLE, LLC\n\nMOTION FOR ADMISSION PRO HAC VICE\n\nTO THE HONORABLE JUDGE OF SAID COURT:\n\nComes now Jordan R. Jaffe , applicant herein, and\n\nmoves this Court to grant admission to the United States District Court for the Western District of\n\nGoogle LLC\n\nTexas pro hac vice to represent in this case, and\n\nwould respectfully show the Court as follows:\n\n1. Applicant is an attorney and a member of the law firm (or practices under the name of)\n\nWilson Sonsini Goodrich & Rosati with offices at:\n\nMailing address: One Market Street, Spear Tower, Suite 3300\n\nCity, State, Zip Code: San Francisco, CA 94105\n\nTelephone: ater947-2000 Facsimile: 866-974-7329\n\nJanuary 10, 2008\n2. Since\n\n. Applicant has been and presently is a\n\nmember of and in good standing with the Bar of the State of C@lifornia\n\nApplicant's bar license number is 254866\n\n3. Applicant has been admitted to practice before the following courts:\n\nCourt: Admission date:\n\nU.S, District Court for N.D. California August 2013\n\nU.S, District Court for $.D. California April 2010\n\nU.S. District Court for E.D. Texas February 2014\n\n\fCase 7:26-mc-00324-LS Document9 Filed 09/03/26 Page 2of4\n\nApplicant is presently a member in good standing of the bars of the courts listed above,\nexcept as provided below (list any court named in the preceding paragraph before which\n\nApplicant is no longer admitted to practice):\n\nN/A\n\nI x have have not previously applied to Appear Pro Hac Vice in this district\n\ncourt in Case[s]: Please see Attachment 1\n\nNumber: on the day of\nNumber: on the day of\nNumber: on the day of ;\n\nApplicant has never been subject to grievance proceedings or involuntary removal\nproceedings while a member of the bar of any state or federal court, except as\n\nprovided:\n\nN/A\n\nApplicant has not been charged, arrested, or convicted of a criminal offense or offenses,\n\nexcept as provided below (omit minor traffic offenses):\n\nN/A\n\nApplicant has read and is familiar with the Local Rules of the Western District of Texas\n\nand will comply with the standards of practice set out therein.\n\fCase 7:26-mc-00324-LS Document9 Filed 09/03/26 Page 3o0f4\n\n9.. Applicant will file an Application for Admission to Practice before the United States\nDistrict Court for the Western District of Texas, if so requested; or Applicant has\nco-counsel in this case who is admitted to practice before the United States District\nCourt for the Western District of Texas.\n\nCo-counsel: #809 M. Storck\n\nMailing address; 900 South Capital of Texas Highway, Las Cimas IV, Fifth Floor\n\nCity, State, Zip Code; Austin, TX 78746\n512-338-5400\n\nTelephone:\n\nShould the Court grant applicant's motion, Applicant shall tender the amount of $100.00 pro hac\nvice fee in compliance with Local Court Rule AT-I(f)(2) [checks made payable to: Clerk, U.S. District\nCourt].\n\nWherefore, Applicant prays that this Court enter an order permitting the admission of\n\nJordan R. Jaffe to the Western District of Texas pro hac vice for this case only.\n\nRespectfully submitted,\nJordan R. Jaffe\nAe\n\nNNN of Applicant]\n\n[s eal of Applicant]\n\nCERTIFICATE OF SERVICE\n\nI hereby certify that I have served a true and correct copy of this motion upon each attorney of\n\nrecord and the original upon the Clerk of Court on this the 3 day of September 2026 |\n\nJordan R\\ Jaffe\ne of Applicant]\n\nf Applicant]\n\fCase 7:26-mc-00324-LS Document9 Filed 09/03/26 Page4of4\n\nAttachment 1\n\nNumber: 6:21-cv-00457 on the 3 day of May, 2021\nNumber: 6:22-cv-00972 on the 16 day of September, 2022\nNumber: 6:23-cv-00197 on the 17 day of March, 2023\nNumber: 6:20-cv-00881 on the 29 day of September, 2020\n\nDocument]\n","ocr_status":1,"date_upload":"2026-09-07T16:40:23.029270-07:00","document_number":"9","attachment_number":null,"pacer_doc_id":"181037343388","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Appear Pro Hac Vice","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492727310/","id":492727310,"tags":[],"absolute_url":"/docket/74667129/9/1/neural-ai-llc-v-google-inc/","date_created":"2026-09-07T16:40:17.721323-07:00","date_modified":"2026-09-10T19:44:50.912472-07:00","sha1":"33b911e5236bbb48add76f184144d7b6e4bbbb8f","page_count":1,"file_size":62785,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.9.1.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.9.1.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-LS Document9-1 Filed 09/03/26 Pagei1of1\n\nUNITED STATES DISTRICT COURT\nWESTERN DISTRICT OF TEXAS\n\nMIDLAND-ODESSA DIVISION\n\nNEURAL AI, LLC\n\nGOOGLE, LLC\n\nORDER\nBE IT REMEMBERED on this day, there was presented to the Court the Motion for\n\nAdmission Pro Hae Vice filed by Jordan R. Jaffe , counsel for\nGoogle LLC\n\n, and the Court, having reviewed the motion, enters\n\nthe following order:\n\nIT IS ORDERED that the Motion for Admission Pro Hac Vice is GRANTED, and\n\nJordan R. Jaffe Google LLC\n\nmay appear on behalf of\n\nin the above case.\n\nIT IS FURTHER ORDERED that Jordan R. Jaffe if he/she\n\nhas not already done so, shall immediately tender the amount of $100.00, made payable to: Clerk, U.S.\nDistrict Court, in compliance with Local Court Rule AT-I(f)(2).\n\nSIGNED this the day of 20\n\nUNITED STATES DISTRICT JUDGE\n","ocr_status":1,"date_upload":"2026-09-07T16:49:24.640620-07:00","document_number":"9","attachment_number":1,"pacer_doc_id":"181037343389","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Proposed Order","acms_document_guid":""}],"date_created":"2026-09-03T17:04:29.253061-07:00","date_modified":"2026-09-07T16:39:00.549501-07:00","date_filed":"2026-09-03","time_filed":"18:39:29","entry_number":9,"recap_sequence_number":"2026-09-03.001","pacer_sequence_number":30,"description":"MOTION to Appear Pro Hac Vice by Jason M. Storck for Admission Pro Hac Vice of Jordan Jaffe ( Filing fee $ 100 receipt number ATXWDC-22598124) by on behalf of Google, Inc.. (Attachments: # 1 Proposed Order)(Storck, Jason) (Entered: 09/03/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/476909959/","id":476909959,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492486039/","id":492486039,"tags":[],"absolute_url":"/docket/74667129/10/neural-ai-llc-v-google-inc/","date_created":"2026-09-03T17:04:28.793817-07:00","date_modified":"2026-09-10T19:33:45.346571-07:00","sha1":"2d58d7f0fee7ff1558dc2d6f2d5b539e7c2efdba","page_count":3,"file_size":111117,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.10.0.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.10.0.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-LS Document10 _ Filed 09/03/26 Pagelof3\n\nUNITED STATES DISTRICT COURT\nWESTERN DISTRICT OF TEXAS\nMIDLAND-ODESSA DIVISION\n\nNEURAL AI, LLC\n\nVS. Case No.: 7:26-mc-00324-LS\nGOOGLE, LLC\n\nMOTION FOR ADMISSION PRO HAC VICE\n\nTO THE HONORABLE JUDGE OF SAID COURT:\n\nComes now DaviG.M- Fox , applicant herein, and\n\nmoves this Court to grant admission to the United States District Court for the Western District of\n\nGoogle LLC\n\nTexas pro hac vice to represent in this case, and\n\nwould respectfully show the Court as follows:\n\n1. Applicant is an attorney and a member of the law firm (or practices under the name of)\n\nWilson Sonsini Goodrich & Rosati with offices at:\n\nOne Market Street, Spear Tower, Suite 3300\n\nMailing address:\n\nCity, State, Zip Code: San Francisco, CA 94105\n\nTelephone: Shed 200 Facsimile: 866-974-7329\n\n2. Since January 17, 2020 , Applicant has been and presently is a\n\nmember of and in good standing with the Bar of the State of California\n330074\n\nApplicant's bar license number is\n\n3. Applicant has been admitted to practice before the following courts:\nCourt: Admission date:\nNorthern District of California 9/15/2021\nNinth Circuit Court of Appeals 6/09/2020\n\nFederal Circuit Court of Appeals 12/16/2022\n\n\fCase 7:26-mc-00324-LS Document10 Filed 09/03/26 Page2of3\n\n4. Applicant is presently a member in good standing of the bars of the courts listed above,\nexcept as provided below (list any court named in the preceding paragraph before which\n\nApplicant is no longer admitted to practice):\n\n5. I have x have not previously applied to Appear Pro Hac Vice in this district\n\ncourt in Case[s]:\n\nNumber: on the day of :\nNumber: on the day of ,\nNumber: on the day of ,\n\n6. Applicant has never been subject to grievance proceedings or involuntary removal\n\nproceedings while a member of the bar of any state or federal court, except as\n\nprovided:\n\n7. Applicant has not been charged, arrested, or convicted of a criminal offense or offenses,\n\nexcept as provided below (omit minor traffic offenses):\n\n8. Applicant has read and is familiar with the Local Rules of the Western District of Texas\n\nand will comply with the standards of practice set out therein.\n\fCase 7:26-mc-00324-LS Document10 _ Filed 09/03/26 Page 3of3\n\n9. Applicant will file an Application for Admission to Practice before the United States\nDistrict Court for the Western District of Texas, if so requested; or Applicant has\nco-counsel in this case who is admitted to practice before the United States District\nCourt for the Western District of Texas.\n\n_ Jason M. Storck\nCo-counsel:\n\nMailing address: 900 South Capital of Texas Highway, Las Cimas IV, Fifth Floor\n\nCity, State, Zip Code; Austin, TX 78746\n512-338-5400\n\nTelephone:\n\nShould the Court grant applicant's motion, Applicant shall tender the amount of $100.00 pro hac\n\nvice fee in compliance with Local Court Rule AT-I(f)(2) [checks made payable to: Clerk, U.S. District\n\nCourt].\n\nWherefore, Applicant prays that this Court enter an order permitting the admission of\n\nwavilsMxP ox to the Western District of Texas pro hac vice for this case only.\n\nRespectfully submitted,\nDavid M. Fox\n\n[printed name of Applicant]\n\nLAUT\n\n[signature of K pplicant]\n\nCERTIFICATE OF SERVICE\n\nI hereby certify that I have served a true and correct copy of this motion upon each attorney of\n\nrecord and the original upon the Clerk of Court on this the 3 __ day of September , 2026 |\n\nDavid M. Fox\n\n[printed name of Applicant]\n\nCozy SK\n\n[signature of Applicant]\n\n","ocr_status":1,"date_upload":"2026-09-07T16:40:21.997951-07:00","document_number":"10","attachment_number":null,"pacer_doc_id":"181037343399","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Appear Pro Hac Vice","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492727311/","id":492727311,"tags":[],"absolute_url":"/docket/74667129/10/1/neural-ai-llc-v-google-inc/","date_created":"2026-09-07T16:40:17.972538-07:00","date_modified":"2026-09-10T19:44:58.903164-07:00","sha1":"b68e10d6f8f08b700cc9e5fd0f27ef31873123ee","page_count":1,"file_size":60149,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.10.1.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.10.1.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-LS Document10-1 _ Filed 09/03/26 Page1of1\n\nUNITED STATES DISTRICT COURT\nWESTERN DISTRICT OF TEXAS\n\nMIDLAND-ODESSA DIVISION\n\nNEURAL AI, LLC\n\nGOOGLE, LLC\n\nORDER\n\nBE IT REMEMBERED on this day, there was presented to the Court the Motion for\n\nAdmission Pro Hae Vice filed by David M. Fox , counsel for\n\nGoogle LLC\n\n, and the Court, having reviewed the motion, enters\n\nthe following order:\n\nIT IS ORDERED that the Motion for Admission Pro Hac Vice is GRANTED, and\n\nDavid M. Fox Google LLC\n\nmay appear on behalf of\n\nin the above case.\n\nIT IS FURTHER ORDERED that D@vid M. Fox if he/she\n\nhas not already done so, shall immediately tender the amount of $100.00, made payable to: Clerk, U.S.\nDistrict Court, in compliance with Local Court Rule AT-I(f)(2).\n\nSIGNED this the day of 20\n\nUNITED STATES DISTRICT JUDGE\n","ocr_status":1,"date_upload":"2026-09-07T16:49:23.607406-07:00","document_number":"10","attachment_number":1,"pacer_doc_id":"181037343400","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Proposed Order","acms_document_guid":""}],"date_created":"2026-09-03T17:04:28.766868-07:00","date_modified":"2026-09-07T16:39:00.612681-07:00","date_filed":"2026-09-03","time_filed":"18:44:46","entry_number":10,"recap_sequence_number":"2026-09-03.002","pacer_sequence_number":32,"description":"MOTION to Appear Pro Hac Vice by Jason M. Storck for Admission Pro Hac Vice of David Fox ( Filing fee $ 100 receipt number ATXWDC-22598138) by on behalf of Google, Inc.. (Attachments: # 1 Proposed Order)(Storck, Jason) (Entered: 09/03/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/476625829/","id":476625829,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/492194117/","id":492194117,"tags":[],"absolute_url":"/docket/74667129/8/neural-ai-llc-v-google-inc/","date_created":"2026-09-01T21:02:51.542744-07:00","date_modified":"2026-09-09T00:39:19.230771-07:00","sha1":"4951ade4ddda5f5d3a5ad7e24336137cf1d873df","page_count":8,"file_size":162490,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.8.0.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.8.0.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":" Case 7:26-mc-00324-LS Document 8 Filed 09/01/26 Page 1 of 8\n\n\n\n\n IN THE UNITED STATES DISTRICT COURT\n FOR THE WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\n\nNEURAL AI, LLC,\n Misc. Case No. 7:26-mc-00324-LS\n Petitioner,\n Principal case pending in Western District of\n v. Texas, Civil Action No. 7:24-cv-00221-LS-\n DTG\nGOOGLE, LLC,\n\n Respondent.\n\n\n NEURAL AI\u2019S REPLY IN SUPPORT OF ITS MOTION TO COMPEL\n COMPLIANCE WITH SUBPOENA SERVED ON THIRD-PARTY GOOGLE, LLC.\n\n\n\n\n i\n\f Case 7:26-mc-00324-LS Document 8 Filed 09/01/26 Page 2 of 8\n\n\n\n\n Google attacks a discovery dispute of its own invention. It exaggerates the original\n\nsubpoenas by reading them as broadly as possible, while ignoring NAI\u2019s repeated efforts to narrow\n\nthem. Over nearly a month, NAI identified a sufficient subset of information, supplied focused\n\ntechnical questions, proposed and revised a declaration in lieu of production and testimony, and\n\nultimately gave Google two options: execute the declaration or produce documents sufficient to\n\nestablish the same facts. Google chose neither. Having stonewalled every accommodation, Google\n\nnow asks the Court to reward its stubbornness. Google cannot reject every narrowing proposal and\n\nthen oppose the motion based on burdens those proposals would have eliminated.\n\nI. NAI SATISFIED LOCAL RULE CV-7(g)\n\n Google\u2019s Rule CV-7(g) argument claims the parties\u2019 many conferences about the subpoenas\n\nconcerned only a declaration, not the twelve requests and five topics. That is wrong. The parties held\n\nmultiple Zoom conferences and exchanged correspondence over nearly a month. See Ex. 12; Ex. 20.\n\nOn July 24, NAI explained the twelve requests and five topics, the information sought, and why it\n\nwas proportional. When Google raised scope and burden, NAI offered focused technical questions\n\nand a declaration capturing the same facts sought by the requests and topics in a shorter, less\n\nburdensome form. Google\u2019s own August 6 email confirms the parties were negotiating the substance\n\nof the subpoenas. Ex. 20 at 5. The declaration was thus not an \u201cancillary\u201d issue, but was NAI\u2019s\n\nproposed compromise on the substance of the subpoenas. That was a sustained effort to resolve the\n\ndispute. Exs. 13\u201314, 20.\n\n NAI also addressed Google\u2019s specific objections. On the first call, Rocco Magni identified a\n\nsufficient subset of information NAI needed, which was the NVIDIA applications and frameworks\n\nGoogle uses and documents sufficient to define its software stack. NAI later offered to narrow every\n\nrequest to documents sufficient to establish the facts in the declaration. Ex. 12 at 1; Ex. 20 at 1. When\n\n\n\n 1\n\f Case 7:26-mc-00324-LS Document 8 Filed 09/01/26 Page 3 of 8\n\n\n\n\nGoogle attempted to rewrite that meet and confer history on the eve of NAI filing, NAI corrected the\n\nrecord: \u201cI\u2019m not sure why you are trying to create a false record. You and I were on a zoom back in\n\nJuly where I talked through a subset of information that we were looking for and said if you provided\n\nthat information \u2026 we would consider Google to have produced sufficient documents.\u201d Opp. Ex. A\n\nat 1. Google tries to erase those discussions by denying them now.\n\n Google\u2019s written objections also made a request-by-request ritual futile. Google objected to\n\nevery document request and every deposition topic. By filing, it had identified no request it would\n\nanswer, produced nothing, and designated no witness. Exs. 9\u201310; Laiche Decl. \u00b6 26. NAI\u2019s certificate\n\nis accurate, and identifies the conferences and correspondence addressing the issues raised in the\n\nmotion. After a month of negotiations, filing was necessary to preserve NAI\u2019s rights. Yet Google\n\nmade no effort to resolve the dispute.\n\n II. THE SUBPOENAS SEEK RELEVANT DISCOVERY\n\n Google\u2019s own evidence establishes relevance. Google\u2019s declarant quotes its Form 10-K\n\ndescribing the \u201cfoundation\u201d of Google\u2019s \u201cfull-stack approach\u201d as \u201cAI-optimized infrastructure\u201d that\n\noffers GPUs, powers Google products such as Search and YouTube, and supports Google Cloud\n\ncustomers. Jaffe Decl. \u00b6 6. NVIDIA likewise states Google Cloud and NVIDIA have collaborated\n\nfor more than a decade, \u201cco-engineering a full-stack AI platform that spans every technology layer.\u201d\n\nEx. 15 at 1. Google Cloud offers NVIDIA GPU instances and deploys NVIDIA-accelerated\n\nsolutions for its customers. Ex. 16 at 1\u20133. This is evidence of deep integration and deployment, not\n\nspeculation based merely on purchasing GPUs.\n\n Google\u2019s configurations go directly to whether customers use the accused hardware and\n\nsoftware to perform the claimed GPU computations and data transfers. Ex. 7 at 2\u20139, 11\u201314. NVIDIA\n\nhas made customer deployment central, contending that NAI must obtain evidence from customers\n\n\n\n\n 2\n\f Case 7:26-mc-00324-LS Document 8 Filed 09/01/26 Page 4 of 8\n\n\n\n\nand end users because NVIDIA does not know how they ultimately configure and operate the\n\naccused products. Ex. 8 \u00b6\u00b6 18\u201323, 87, 131, 171; Laiche Decl. \u00b6\u00b6 24\u201325. Only Google can supply\n\nGoogle\u2019s internal deployment facts. Moreover, NAI does not need to prove infringement before it\n\nasks Google the question. That is not how discovery works.\n\nIII. THE SUBPOENAS ARE TAILORED AND WERE REPEATEDLY NARROWED\n\n Google attacks the broadest imaginable reading of the subpoenas, not the discovery NAI\n\nactually sought. Requests 1\u20135 seek documents sufficient to identify or show the relevant software\n\nstack, NVIDIA software and sample code Google uses, how Google software interfaces with\n\nNVIDIA functionality, and the architecture and data flow of systems using NVIDIA GPUs. Ex. 5 at\n\n12\u201314. \u201cDocuments sufficient to show\u201d is an express limitation. NAI narrowed further by offering\n\nto accept only documents sufficient to establish the facts in the three-page revised declaration. Ex.\n\n20. That does not require every document, source-code file, or historical software version.\n\n Requests 6\u201312 likewise seek operational facts, not Google\u2019s legal conclusions. They ask\n\nwhat Google\u2019s systems do, including whether neural-network computations occur; how pointers,\n\nbuffers, inputs, outputs, and intermediate results move through memory; and how computations are\n\nscheduled, synchronized, and executed. Ex. 5 at 14\u201317. A fact witness explaining system operation\n\nneed not offer patent-law opinions. The five deposition topics cover the same subjects and provide\n\nan alternative means of filling factual gaps. Id. at 24.\n\n Google\u2019s burden evidence is entirely derivative of its inflated reading. Google\u2019s \u201c240\n\nproducts\u201d refrain is a red herring. The definition of \u201cNVIDIA GPUs\u201d tracks the accused products\n\nidentified in NAI\u2019s infringement contentions and thus the scope of NVIDIA\u2019s alleged infringement.\n\nEx. 5 at 6\u20138; Ex. 7 at 2\u20139. But Google need not investigate GPUs it does not use. It knows which\n\nNVIDIA GPUs it purchases and deploys, and its procurement and asset records should identify that\n\n\n\n\n 3\n\f Case 7:26-mc-00324-LS Document 8 Filed 09/01/26 Page 5 of 8\n\n\n\n\nsubset readily. And Google offers no basis to suggest that each GPU model runs a unique, bespoke\n\nsoftware stack. The same frameworks, libraries, and APIs are likely deployed across most\u2014if not\n\nall\u2014NVIDIA GPU models. Thus, identifying the relevant GPUs and shared software configurations\n\ndoes not transform one request into \u201cover 240 requests\u201d as Google speculates.\n\n The Jaffe declaration also does not substantiate burden. It is from outside counsel, not a\n\nGoogle technical employee or custodian, and identifies no search performed, technical personnel\n\nconsulted, custodians, repositories, estimated hours, or costs. Instead, it infers from Alphabet\u2019s\n\nemployee count and broad use of AI that \u201cany number of thousands\u201d of employees might be involved\n\nand compliance might take months. Jaffe Decl. \u00b6\u00b6 5\u20138. It never actually says Google uses most of\n\nthe 240 GPUs, thousands of employees possess responsive information, or NAI\u2019s narrowed search\n\nwould actually take months. Conjecture does not satisfy Google\u2019s obligation to state specifically\n\nhow burden relates to each request. See 611 Carpenter LLC v. Atlantic Casualty Ins. Co., 2024 WL\n\n1977160, at *1 (W.D. Tex. Apr. 30, 2024) (\u201cA party objecting to discovery must state with\n\nspecificity the objection and how it relates to the particular request being opposed, and not merely\n\nthat it is overly broad and burdensome.\u201d).\n\n Google\u2019s proprietary-information objection is equally abstract. To be clear, NAI does not\n\nneed access to Google\u2019s unique trade-secret code. NAI needs to know how Google is incorporating\n\nNVIDIA\u2019s code, what functionalities it is invoking, and what modifications, if any, it is making.\n\nNAI thus seeks documents sufficient to show identified deployment of NVIDIA software and\n\nexecution facts. The existing protective order and tailored protections can address confidential\n\nmaterial, and Rule 45 permits production under specified conditions. Google identifies no specific\n\ntrade secret that would be disclosed, no specific document that cannot be protected, or reason\n\nredaction would be inadequate. Ex. 5 at 3\u20135; Opp. at 8\u201310; Jaffe Decl. \u00b6 8.\n\n\n\n\n 4\n\f Case 7:26-mc-00324-LS Document 8 Filed 09/01/26 Page 6 of 8\n\n\n\n\n Moreover, Google\u2019s time-period objection lacks merit. The time period is tied to the case.\n\nSeptember 13, 2018 begins the damages period for the infringement conduct at issue. Google offers\n\nno evidence that relevant records are inaccessible or that the narrowed \u201cdocuments sufficient\u201d\n\nstandard creates burden.\n\n Most importantly, NAI took every reasonable step Rule 45 requires to minimize burden. It\n\ndistilled the subpoenas into focused technical questions, offered to accept a declaration in lieu of\n\nany production or testimony, invited Google to revise the declaration for accuracy, revised it to\n\naddress Google\u2019s stated concern, and ultimately gave Google two options: Google could either\n\n\u201c(1) execute[] a revised declaration addressing the issues identified in the [draft declaration]\n\nwithout material gaps, or (2) produce[] documents sufficient to establish each of those issues.\u201d Ex.\n\n20 at 1; Exs. 13\u201314, 20\u201321; Laiche Decl. \u00b6\u00b6 21\u201326. Google chose neither. It answered no question,\n\nproposed no language, produced no document, designated no witness, and offered no narrower\n\nalternative of its own. NAI repeatedly narrowed and Google categorically refused to comply.\n\n The Court can also enforce the narrowed relief NAI offered, which is \u201cproduc[ing]\n\ndocuments sufficient to establish each of [the] issues\u201d in NAI\u2019s \u201crevised declaration.\u201d Ex. 20 at 1.\n\nOnly material gaps would require testimony on the corresponding topics. That sequence protects\n\nGoogle without permitting it to avoid relevant discovery by refusing every form of compliance.\n\nIV. CONCLUSION\n\n The Court should grant NAI\u2019s Motion. At minimum, it should compel Google to produce\n\n documents sufficient to establish the facts addressed in NAI\u2019s draft declaration and designate a\n\n witness to testify regarding any remaining gaps. Ex. 14.\n\n\n\n\n 5\n\f Case 7:26-mc-00324-LS Document 8 Filed 09/01/26 Page 7 of 8\n\n\n\n\nDated: September 1, 2026\n\n\n Respectfully submitted,\n\n /s/ Rocco Magni\n Max L. Tribble\n Texas State Bar 20213950\n Brian D. Melton\n Texas State Bar 24010620\n Rocco Magni\n Texas State Bar 24092745\n Samuel Drezdzon\n Texas State Bar 24117374\n SUSMAN GODFREY L.L.P.\n 1000 Louisiana\n Suite 5100\n Houston, TX 77002\n Telephone: (713) 651-9366\n Facsimile: (713) 654-6666\n mtribble@susmangodfrey.com\n bmelton@susmangodfrey.com\n rmagni@susmangodfrey.com\n sdrezdzon@susmangodfrey.com\n\n Tamar Lusztig\n NY State Bar 5125174\n Emily Portuguese\n NY State Bar 5920327\n One Manhattan West, 50th Floor\n New York, NY 10001\n tlusztig@susmangodfrey.com\n eportuguese@susmangodfrey.com\n\n Tanner Laiche\n WA State Bar 60450\n 401 Union Street, Suite 3000\n Seattle, WA 98101\n tlaiche@susmangodfrey.com\n\n Attorneys for Petitioner Neural AI, LLC\n\n\n\n\n 6\n\f Case 7:26-mc-00324-LS Document 8 Filed 09/01/26 Page 8 of 8\n\n\n\n\n CERTIFICATE OF SERVICE\n\n I hereby certify that on September 1, 2026, I electronically filed the foregoing document\n\nwith the Clerk of Court using the CM/ECF system, which will send notification of such filing to\n\ncounsel for Google LLC.\n\n /s/ Rocco Magni\n Rocco Magni\n\n\n\n\n 7\n\f","ocr_status":2,"date_upload":"2026-09-02T09:10:39.238530-07:00","document_number":"8","attachment_number":null,"pacer_doc_id":"181037317327","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Reply to Response to Motion","acms_document_guid":""}],"date_created":"2026-09-01T21:02:51.518830-07:00","date_modified":"2026-09-02T09:10:20.423001-07:00","date_filed":"2026-09-01","time_filed":"22:32:03","entry_number":8,"recap_sequence_number":"2026-09-01.001","pacer_sequence_number":27,"description":"REPLY to Response to Motion, filed by Neural AI, LLC, re 1 MOTION to Compel Compliance with Subpoena Served on Third-Party Google, LLC filed by Petitioner Neural AI, LLC (Magni, Rocco) (Entered: 09/01/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/475788805/","id":475788805,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/491331971/","id":491331971,"tags":[],"absolute_url":"/docket/74667129/7/neural-ai-llc-v-google-inc/","date_created":"2026-08-25T16:17:17.583136-07:00","date_modified":"2026-09-08T10:16:01.832584-07:00","sha1":"8d405b853882cfb4995b5f1452731febca330d2c","page_count":14,"file_size":92809,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.7.0.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.7.0.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":" Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 1 of 14\n\n\n\n\n IN THE UNITED STATES DISTRICT COURT\n FOR THE WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\nNEURAL AI, LLC, )\n )\n Petitioner, )\n )\n v. ) MISC. CASE NO.: 7:26-mc-00324-LS\n )\nGOOGLE, LLC, ) Underlying Case: Texas Western District\n ) Court, Civil Action No. 7:24-cv-00221-\n Respondent. ) ADA-DTG\n )\n\n\n MEMORANDUM IN RESPONSE TO PETITIONER\u2019S MOTION TO COMPEL\n COMPLIANCE WITH SUBPOENAS SERVED ON NON-PARTY GOOGLE LLC\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 2 of 14\n\n\n\n\n TABLE OF CONTENTS\n\n Page\n\nI. INTRODUCTION .............................................................................................................. 1\n\nII. FACTUAL BACKGROUND ............................................................................................. 3\n\nIII. ARGUMENT ...................................................................................................................... 4\n\n A. The Motion Does Not Comply with Local Rule CV-7(g) ...................................... 4\n B. The Subpoenas Do Not Comply with Federal Rule 45........................................... 6\n\nIV. CONCLUSION ................................................................................................................. 10\n\n\n\n\n i\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 3 of 14\n\n\n\n\nI. INTRODUCTION\n\n Neural AI, LLC (\u201cNeural\u201d) has filed at least nine separate actions to compel discovery.1\n\nThe instant motion thus does not exist on an island: the subpoena to produce documents and to\n\ntestify (\u201cSubpoenas\u201d) to which Google LLC (\u201cGoogle\u201d) objects is part of a larger litigation\n\npattern by Neural seeking discovery that is overbroad, unduly burdensome, and not proportional\n\nto the needs of its litigation against NVIDIA. In each of these separate actions, Neural served\n\nnearly identical subpoenas on non-parties, and when each non-party fairly objected, Neural filed\n\nnearly identical motions to compel. It is unclear whether Neural has taken a moment to reflect\n\nand consider why each of the non-parties \u201cobjected to every request and deposition topic,\u201d see,\n\ne.g., Neural AI v. xAI, 7:26-mc-00319-DC, Dkt. 1, at 1 (W.D. Tex. Aug. 17, 2026), but one thing\n\nremains constant across these actions: Neural\u2019s unreasonable approach to non-party discovery.\n\n In this action, Google timely objected to Neural\u2019s boundless requests seeking information\n\nabout roughly 240 devices over an 8-year timeframe. The parties then engaged in a meet-and-\n\nconfer process, during which Neural never addressed Google\u2019s objections nor narrowed a single\n\ndocument request or deposition topic. Instead, Neural focused on having Google sign a\n\ndeclaration \u201cin lieu of further document production and/or deposition testimony.\u201d Mot. at 4.\n\nThe meet-and-confer process thus never addressed Google\u2019s objections to the Subpoenas;\n\ninstead, Neural filed a precipitate motion to compel just hours after providing Google a \u201crevised\n\ndeclaration\u201d with language Google had never seen. It follows that Neural\u2019s rush to the\n\n\n\n1\n See Neural AI v. Meta Platforms, No. 7:26-mc-00327-LS (W.D. Tex. Aug. 19, 2026);\nNeural AI v. CoreWeave, No. 7:26-mc-00323-LS (W.D. Tex. Aug. 18, 2026); Neural AI v.\nOracle, No. 7:26-mc-00325-DC (W.D. Tex. Aug. 18, 2026); Neural AI v. xAI, No. 7:26-mc-\n00319-DC (W.D. Tex. Aug. 17, 2026); Neural AI v. Tesla, No. 7:26-mc-00318-LS (W.D. Tex.\nAug. 17, 2026); Neural AI v. OAI Int\u2019l., Inc., 3:26-mc-80261-AGT (N.D. Cal., Aug. 17, 2026);\nNeural AI v. Amazon.com, No. 7:26-mc-00241-LS (W.D. Tex. June 24, 2026); Neural AI v.\nMicrosoft, No. 7:26-mc-00242-LS (W.D. Tex. June 24, 2026).\n\n\n 1\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 4 of 14\n\n\n\n\ncourthouse was not driven by an impasse between the parties, but rather by the deadline in the\n\nunderlying litigation against NVIDIA, which Neural openly admitted. Dkt. 1-21 at 2 (Aug. 18\n\nemail from T. Laiche) (\u201cGiven today\u2019s deadline, we intend to file a motion solely to preserve our\n\nrights and avoid any potential waiver of discovery from Google.\u201d). But filing a discovery\n\nmotion to \u201cpreserve rights\u201d does not comply with Local Rule CV-7(g), which requires that\n\n\u201ccounsel for the parties have conferred in a good-faith attempt to resolve the matter by\n\nagreement.\u201d And, as Google explained in correspondence before Neural filed its motion, the\n\nparties did not confer on the \u201crevised declaration\u201d nor \u201cany of the specific requests or topics\u201d in\n\nthe Subpoenas. Ex. A at 4.2 The Court should deny the instant motion because Neural failed to\n\ncomply with Local Rule CV-7(g).\n\n The Court should also deny the motion because the Subpoenas are overly broad, unduly\n\nburdensome, and disproportionate to needs of its litigation against NVIDIA, especially in view\n\nof Neural making requests of a non-party. See Fed. R. Civ. P. 45. For starters, Neural has not\n\ndemonstrated that the requested discovery is relevant. Neural simply guesses that Google\n\npossesses relevant information merely because Google buys NVIDIA GPUs. But this type of\n\n\u201cfishing expedition\u201d is inappropriate, especially when directed to non-parties. Micro Motion,\n\nInc. v. Kane Steel Co., Inc., 894 F.2d 1318, 1327-28 (Fed. Cir. 1990). And, while Neural says\n\nthe Subpoenas seek \u201ctargeted\u201d documents, Mot. 1, 5, the opposite is true. Indeed, the very first\n\nDefinition in the Subpoenas\u2014defining the term \u201cNVIDIA GPUs\u201d\u2014demonstrates the\n\nunreasonableness of the various requests Neural makes. According to Neural, the term\n\n\u201cNVIDIA GPUs\u201d means nine different \u201carchitectures\u201d of NVIDIA graphics processing units,\n\nwhich include over 240 devices. Dkt. 1-6 at 6\u20138. Even more, Neural included this definition in\n\n\n\n2\n Neural omitted this correspondence from its motion.\n\n\n 2\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 5 of 14\n\n\n\n\n11 of 12 document requests, which would necessarily require Google to produce \u201cvoluminous\u201d\n\nrecords. See, e.g., Lopez v. State Farm Lloyds, 348 F.R.D. 419, 429 (W.D. Tex. 2025). Google\n\nrespectfully requests that the Court deny Neural\u2019s motion.\n\nII. FACTUAL BACKGROUND\n\n Neural served Google with the Subpoenas on June 25, 2026, and Google timely served\n\nwritten objections on July 21, 2026. Contrary to Neural\u2019s presentation of the facts, Google\u2019s\n\nobjections were not \u201cboilerplate,\u201d Mot. at 3, but instead explained in detail why each request or\n\ntopic was improper. Dkt. 1-10 at 10\u201331, Dkt. 1-11 at 9\u201314. Google also offered to meet-and-\n\nconfer to discuss each document request and deposition topic. Id.\n\n The parties conferred on July 24, 2026. Rather than address Google\u2019s objections to the\n\nSubpoenas, Neural sent over a list of questions and a template declaration for Google\u2019s review,\n\nsaying Neural would \u201cconsider accepting the declaration in lieu of further document production\n\nand/or deposition testimony, subject to resolving any material gaps.\u201d Dkt. 1-21 at 7\u20138 (Aug. 6\n\nemail from R. Magni). Google responded that it might be able to \u201cprovide a declaration within a\n\nmore reasonable scope.\u201d Id. at 7 (Aug. 6 email from J. Jaffe). Neural agreed, and asked for\n\n\u201cproposed edits to the declaration as soon as possible[.]\u201d Id. at 4 (Aug. 11 email from T.\n\nLaiche). Google responded two days later that it had an update and requested a call with Neural,\n\noffering times that day and the following day. Id. at 3\u20134 (Aug. 13 email from J. Jaffe). Neural\n\ndid not respond until that weekend. Id. at 3 (Aug. 16 email from T. Laiche). Google responded\n\nthe next day, and the parties conferred that same day. Id. at 2 (Aug. 17 email from J. Jaffe).\n\n After conferring on August 17, Neural sent Google two follow-up emails on August 18.\n\nIn the first email, Neural wrote that it would file its motion to compel that day \u201cto preserve our\n\nrights and avoid any potential waiver of discovery from Google.\u201d Id. at 1\u20132 (Aug. 18 email from\n\nT. Laiche). In the second email, sent about five hours later, Neural attached a \u201crevised\n\n\n 3\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 6 of 14\n\n\n\n\ndeclaration,\u201d which Neural said it believed \u201caccurately reflects Google\u2019s operations.\u201d Id. at 1\n\n(Aug. 18 email from T. Laiche). As Google pointed out in an email sent before Neural filed its\n\nmotion, the parties never conferred regarding the \u201crevised declaration\u201d nor \u201cany of the specific\n\nrequests or topics\u201d in the Subpoenas. Ex. A at 3\u20134. (Aug. 18 email from J. Jaffe) (\u201cNeedless to\n\nsay, Google and Neural AI have not met and conferred regarding Neural AI\u2019s latest positions and\n\nrevised declaration.\u201d). Because of this, Google explained that Neural\u2019s decision to file a\n\ndiscovery motion was premature and in violation of this Court\u2019s local rules. Id.\n\nIII. ARGUMENT\n\n Neural\u2019s motion to compel should be denied because the motion does not comply with\n\nthis Court\u2019s local rules and because the Subpoenas do not comply with Federal Rule 45.\n\n A. The Motion Does Not Comply with Local Rule CV-7(g)\n\n Local Rule CV-7(g) provides, in relevant part:\n\n The court may refuse to hear or may deny a nondispositive motion\n unless the movant advises the court within the body of the motion\n that counsel for the parties have conferred in a good-faith attempt to\n resolve the matter by agreement and certifies the specific reason that\n no agreement could be made.\n\n Here, Neural\u2019s certificate of conference stated the following:\n\n The undersigned certifies that counsel for Neural AI, LLC conferred\n in good faith with counsel for non-party Google, LLC regarding the\n issues raised in this Motion, including Zoom conferences on or\n about July 25, August 1, and August 17, 2026, and related email\n correspondence. Despite those efforts, the parties were unable to\n resolve the dispute.\n\nMot. at 12. The certificate is inaccurate. Counsel for Neural and Google did not confer\n\n\u201cregarding the issues raised in this Motion.\u201d Id. As the record shows, the parties spent their time\n\ndiscussing the scope of the declaration Neural wanted Google to sign; Google\u2019s general and\n\nspecific objections to the discovery sought in the Subpoenas were never addressed. Yet the\n\n\n\n 4\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 7 of 14\n\n\n\n\n\u201cissues raised in this Motion\u201d are entirely about the discovery sought in the Subpoenas. Mot. at\n\n6\u201310 (requesting that the Court compel Google to produce documents responsive to Requests 1\u2013\n\n12 and to produce a witness on Deposition Topics 1\u20135).\n\n There was ample opportunity for Neural to engage with Google about the objections\n\nGoogle raised. Google provided Neural with both general and specific objections to the\n\nSubpoenas, including, inter alia, that they seek information \u201cnot proportionate to the needs of the\n\ncase,\u201d Dkt. 1-10 at 3, use vague and overbroad definitions like the one for \u201cNVIDIA GPUs,\u201d id.\n\nat 4, seek \u201csource code or the equivalent of a full source code review,\u201d id. at 6\u20137, and impose an\n\nimproper \u201ctemporal scope of September 13, 2018 to the present,\u201d id. at 8. See also id. at 10\u201331\n\n(specific objections to document requests); id. Dkt. 1-11 at 9\u201314 (specific objections to\n\ndeposition topics). The parties\u2019 discussions nevertheless focused entirely on the ancillary\n\ndeclaration that Neural wanted Google to sign. But the declaration is not what \u201cthe issues raised\n\nin this Motion\u201d are about, Mot. at 12; and Neural\u2019s failure to confer with Google on either the\n\n\u201crevised declaration\u201d or Google\u2019s objections is an independent ground to deny the motion. See\n\nGonzalez v. Int\u2019l Med. Devices, Inc., No. 1:24-cv-00982, 2025 WL 3453956, at *2 (W.D. Tex.\n\nNov. 14, 2025) (\u201cGonzalez has not satisfied the conference requirement of Local Rule CV-7(g)\n\nbecause he has not actually talked with Defendants about the alleged deficiencies.\u201d).\n\n Whether driven by expediency or some other litigation strategy,3 Neural ignored the local\n\nrules, which required the parties to discuss \u201ceach item\u201d underlying the motion to compel before\n\nrunning to the courthouse. Anzures v. Prologis Texas I LLC, 300 F.R.D. 314, 315\u201316 (W.D.\n\n\n\n\n3\n Neural sought a similar \u201cdeclaration\u201d from the other non-parties it is suing in federal\ncourt for discovery. See, e.g., Neural AI v. Meta Platforms, No. 7:26-mc-00327-LS, Dkt. 1 at 1\n(explaining that Neural supplied \u201ca draft declaration\u201d and \u201cinvited Meta to propose revisions or\nprovide equivalent information in lieu of broader discovery\u201d).\n\n\n 5\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 8 of 14\n\n\n\n\nTex. 2012). That did not happen here. As a consequence, Neural\u2019s premature motion wastes\n\nboth party and court resources. Id. at 316 (\u201cIt appears that it may require several hours of court\n\ntime to resolve the numerous issues raised; it seems logical that the parties will have spent an\n\nequal or greater amount of time attempting to resolve the issues.\u201d); In re Presto, 358 B.R. 290,\n\n293 (S.D. Tex. 2006) (\u201cIt is vitally important that counsel confer with one another in good faith,\n\nand so represent to the Court, before taking up court time. . .\u201d). At bottom, Neural\u2019s certificate\n\nthat the parties \u201cconferred in a good-faith attempt to resolve the matter\u201d cannot be squared with\n\nthe record, which shows that the parties never coffered on \u201cthe matter\u201d now before the Court,\n\ni.e., the twelve document requests and five deposition topics. Ex. A at 2; id. at 4 (\u201cWe have not\n\ndiscussed any of the specific requests or topics at any point. Instead, Neural AI has chosen to\n\nfocus on a form declaration, of which it only provided a revised version earlier today.\u201d). Neural\n\nfailed to comply with Local Rule CV-7(g).\n\n B. The Subpoenas Do Not Comply with Federal Rule 45\n\n If the Court does not deny the instant motion based on Neural\u2019s failure to appropriately\n\nmeet and confer, Google respectfully requests that it deny the motion on substantive grounds.\n\n The Subpoenas fail to comply with Federal Rule 45. To begin, Neural has not\n\ndemonstrated the requested discovery is relevant. Neural says it seeks evidence to support\n\nindirect infringement allegations against NVIDIA, but Neural has not shown an evidentiary basis\n\nthat Google uses NVIDIA GPUs or software in an allegedly infringing configuration. Neural is\n\nsimply guessing that Google possesses relevant information merely because Google buys\n\nNVIDIA GPUs. This is laid bare by Neural\u2019s indiscriminate \u201cshotgun\u201d approach to non-party\n\ndiscovery, in which it has served carbon-copy subpoenas and filed undifferentiated motions\n\nagainst a wide swath of third parties. Indeed, several of the requests ask whether Google uses\n\nNVIDIA products in a particular way. This type of speculation is improper, particularly against\n\n\n 6\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 9 of 14\n\n\n\n\na non-party. \u201cA litigant may not engage in merely speculative inquiries in the guise of relevant\n\ndiscovery.\u201d Micro Motion, 894 F.2d at 1327-28 (rejecting third party subpoena that was a\n\n\u201cfishing expedition.\u201d); see also Strong v. Paradise, No. 3:23-cv-2847-K, 2025 WL 1811766, at\n\n*3 (N.D. Tex. July 1, 2025) (\u201c[U]nder Rule 45, non-parties have greater protections from\n\ndiscovery than parties do.\u201d) (internal quotations omitted).4\n\n The Subpoenas are also unduly burdensome, for at least the following reasons:\n\n Temporal Scope: Neural argues that the Subpoenas are \u201climited\u201d to September 13, 2018\n\nto the present.\u201d Mot. at 9. An eight-year period is not \u201climited,\u201d and enhances the burden on\n\nnon-party Google. See, e.g., Treadway v. Otero, No. 2:19-cv-244, 2020 WL 602225, at *3 (S.D.\n\nTex. Feb. 7, 2020) (\u201cPlaintiff\u2019s request for production of these documents for a period of eight\n\nyears, from 2010-2018, is unduly burdensome.\u201d).\n\n NVIDIA GPUs: Eleven of the twelve document requests rely on Neural\u2019s definition of\n\n\u201cNVIDIA GPUs,\u201d which in effect turns each individual document request into \u201cover 240\n\nrequests.\u201d See, e.g., Dkt. 1-10 at 31. Take for example Request No. 1, which seeks documents\n\n\u201csufficient to identify all software, frameworks, libraries, APIs, scripts, Source Code,\n\nconfiguration files, and custom code You use to perform computations on NVIDIA GPUs.\u201d Dkt.\n\n1-6 at 13. To properly respond to this request, Google would need to identify all [1] software,\n\n[2] frameworks, [3] libraries, [4] APIs, [5] scripts, [6] Source Code, [7] configuration files, and\n\n[8] custom code that Google uses to perform computations on over 240 products. Responding to\n\nthis request (and the ten others using the \u201cNVIDIA GPUs\u201d definition) would require Google to\n\nproduce \u201cvoluminous\u201d records that are spread out across multiple departments at the company.\n\n\n4\n Google further disagrees with Neural\u2019s view that this district is the appropriate place for\ncompliance, Fed. R. Civ. P. 45(c), but given the other manifest deficiencies the subpoenas, is not\nrelying on that issue here. See Dkts. 1-10, 1-11 at 2-3.\n\n\n 7\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 10 of 14\n\n\n\n\nSee State Farm Lloyds, 348 F.R.D. at 429. Jaffe Decl. \u00b6 8. Requiring Google to search for\n\ninformation associated with \u201cNVIDIA GPUs\u201d over an eight-year period would be akin to asking\n\nFord to catalog how it uses every steering wheel, and every associated blueprint for each car it\n\nmakes that includes a steering wheel, over almost a decade.\n\n Document Request No. 1: Request No. 1 is patently overbroad and unduly burdensome.\n\nIt requests: \u201cDocuments sufficient to identify all software, frameworks, libraries, APIs, scripts,\n\nSource Code, configuration files, and custom code You use to perform computations on NVIDIA\n\nGPUs.\u201d NVIDIA GPUS refers to the three-page definition discussed above, and \u201cSource Code\u201d\n\nis defined to include \u201call associated files necessary to understand, compile, and execute the code,\n\nsuch as scripts, header files, makefiles, configuration files, and documentation.\u201d Dkt. 1-6 at 10.\n\n\u201cSource Code\u201d is further defined to include \u201call versions and revisions relevant to the time\n\nperiods and subject matter.\u201d This request thus seeks an exhaustive catalog of every piece of\n\nsoftware, framework, library, API, script, source code, configuration file, and custom code that\n\nGoogle purportedly uses with at least ~240 NVIDIA GPUs and \u201cevery version\u201d of any software\n\nthat goes along with it for the past eight years. To even begin to assess how to comply with this\n\nrequest across the entirety of Google would be nearly impossible, and certainly could not be\n\naccomplished within any realistic timeframe. Jaffe Decl. \u00b6 8. And this is for documentation\n\nwhich has not even been shown to be relevant or at a minimum proportional to the needs of the\n\ncase under Rule 26.\n\n The request further seeks Google\u2019s highly proprietary software and workflow for its AI\n\nsoftware and services, comprising Google trade secrets. Google should not be required to\n\ndisclose some of its most highly confidential and competitive technical information without a\n\nsufficient demonstration of relevance and proportionality. See Leonardo Worldwide Corp. v.\n\n\n\n\n 8\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 11 of 14\n\n\n\n\nPegasus Sols., Inc., 2015 WL 13469920, at *4 (N.D. Tex. Apr. 16, 2015) (\u201cAlthough the request\n\nmay be tangentially relevant to a defense in the case, the request seems likely to procure far more\n\nirrelevant, burdensome, and potentially confidential information than it would procure\n\ninformation relevant to this action.\u201d).\n\n Document Requests Nos. 2\u20134: These requests are objectionable for the same reasons as\n\nDocument Request No. 1. These requests are aimed at a laundry list of NVIDIA software or\n\nundefined sample code from NVIDIA. Request No. 4 goes so far as to seek information about\n\n\u201cany software\u201d Google uses \u201cto perform computations on NVIDIA GPUs.\u201d Dkt. 1-6 at 13. As\n\nwith Request No. 1, these requests are boundless dragnets that lack any defining parameters or\n\nlogical boundaries. Compliance would require a sprawling, unfocused investigation across the\n\nentirety of Google. Jaffe Decl. \u00b6 8. The rules do not license such an indiscriminate fishing\n\nexpedition, particularly against a non-party. Micro Motion, 894 F.2d at 1327-28; Paradise, 2025\n\nWL 1811766, at *3.\n\n Document Request No. 5: This request is even broader than Document Request No. 1.\n\nThis request seeks documents to describe the architecture of \u201cany system\u201d at Google that uses\n\nNVIDIA GPUs to perform computations, including every version of source code over the past\n\neight-years. For a company at the forefront of AI like Google, this would be a Herculean task.\n\nNeural has not, and cannot, justify the relevance of this request when compared to the\n\ndisproportionate burden imposed on Google.\n\n Document Requests No. 6\u201312: These requests are Neural\u2019s attempt to shift the burden\n\nto Google to substantiate Neural\u2019s infringement claims. Compare Dkt. 1-6 at 14 (\u201cDocuments\n\nsufficient to show whether You use a pointer to data stored in memory\u2026 swapping an input\n\npointer with the pointer to data output from a GPU computation\u2026\u201d) with U.S. Patent No.\n\n\n\n\n 9\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 12 of 14\n\n\n\n\n8,648,867 at col. 14:40\u201352 (claiming an accelerator controller . . . to swap the first pointer and\n\nthe second pointer\u201d). This is an unabashed fishing expedition with no demonstrated relevance to\n\nGoogle, Micro Motion, 894 F.2d at 1327\u201328, which also imposes undue burden on Google\n\nbecause of the highly technical (and legal) nature of the requests.\n\n Deposition Topics Nos. 1\u20135: As Neural readily admits, the deposition topics seek\n\ninformation \u201con the same subjects as the document requests,\u201d Mot. at 13, so necessarily suffer\n\nfrom the same flaws as the document requests, and in some instances even more so. For\n\nexample, Topic No. 1 asks Google to provide a deponent to testify about 28 different \u201cNVIDIA\n\nsoftware and libraries\u201d used across Google\u2019s entire computing infrastructure, Dkt. 1-6 at 24;\n\nTopic No. 2 adopts the unreasonably broad definition of \u201cSource Code,\u201d id.; Topic No. 3 asks for\n\na witness to testify about every \u201ccustomization\u201d or \u201cdata input\u201d Google has made to any\n\nNVIDIA software (whatever that means), and a description of this so-called \u201cdata input,\u201d id.;\n\nTopic No. 4 requests that a witness testify to the identity of all software at Google \u201cthat uses\n\nNVIDIA GPUs to perform computation,\u201d which as discussed above, would cover over 240\n\nproducts, id., and Topic No. 5 is analogous to Document Requests No. 6\u201312, seeking highly\n\ntechnical information and, arguably, a deponent with experience in patent law who can testify to\n\nthe claim limitations at issue in Neural\u2019s underlying litigation against NVIDIA. The deposition\n\ntopics are improper.\n\nIV. CONCLUSION\n\n For the foregoing reasons, Google respectfully requests that the Court deny Neural\u2019s\n\nmotion to compel.5\n\n\n\n5\n Google reserves the right to seek its fees under Fed. R. Civ. P. 45(d)(1) based on Neural\u2019s\nfailure to take reasonable steps to avoid imposing undue burden or expense on a person subject\nto the subpoena.\n\n\n 10\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 13 of 14\n\n\n\n\nDated: August 25, 2026 /s/ Jason M. Storck\n\n\n Jordan R. Jaffe (pro hac vice forthcoming)\n jjaffe@wsgr.com\n David Fox (pro hac vice forthcoming)\n dfox@wsgr.com\n WILSON SONSINI GOODRICH & ROSATI\n One Market Street, Spear Tower, Suite 3300\n San Francisco, CA 94105\n Telephone: (415) 947-2000\n\n Jason M. Storck, Texas Bar No. 24037559\n jstorck@wsgr.com\n WILSON SONSINI GOODRICH & ROSATI\n 900 South Capital of Texas Highway\n Las Cimas IV, Fifth Floor\n Austin, TX 78746\n\n\n Attorneys for Respondent Google LLC\n\n\n\n\n 11\n\f Case 7:26-mc-00324-LS Document 7 Filed 08/25/26 Page 14 of 14\n\n\n\n\n CERTIFICATE OF SERVICE\n\n The undersigned certifies that, on August 25, 2026, all counsel of record are being served\n\nwith a copy of this document via CM/ECF to the following:\n\n Susman Godfrey\n\n Brian D. Melton\n 1000 Louisiana St.\n Suite 5100\n Houston, TX 77002\n bmelton@susmangodfrey.com\n\n Max L. Tribble , Jr.\n 1000 Louisiana\n Suite 5100\n Houston, TX 77002-5096\n mtribble@susmangodfrey.com\n 713-653-7820\n\n Rocco Magni\n 1000 Louisiana, Suite 5100\n Houston, TX 77002-5096\n rmagni@susmangodfrey.com\n\n Tanner H. Laiche\n 401 Union St., Suite 3000\n Seattle, WA 98101\n tlaiche@susmangodfrey.com\n 206-516-3880\n\n Attorneys for Petitioner Neural AI, LLC\n\n /s/ Jason M. Storck\n Jason M. Storck\n\n\n\n\n 12\n\f","ocr_status":2,"date_upload":"2026-08-26T06:55:16.653097-07:00","document_number":"7","attachment_number":null,"pacer_doc_id":"181037269164","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Memorandum in Opposition to Motion","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/491364353/","id":491364353,"tags":[],"absolute_url":"/docket/74667129/7/1/neural-ai-llc-v-google-inc/","date_created":"2026-08-26T06:55:31.773727-07:00","date_modified":"2026-09-08T11:07:21.349304-07:00","sha1":"646d3294c2c5005dd3e85a46162e4eb5ee17c2a4","page_count":5,"file_size":42346,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.7.1.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.7.1.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":" Case 7:26-mc-00324-LS Document 7-1 Filed 08/25/26 Page 1 of 5\n\n\n\n\n IN THE UNITED STATES DISTRICT COURT\n FOR THE WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\nNEURAL AI, LLC, )\n )\n Petitioner, )\n )\n v. ) MISC. CASE NO.: 7:26-mc-00324-LS\n )\nGOOGLE, LLC, ) Underlying Case: Texas Western District\n ) Court, Civil Action No. 7:24-cv-00221-\n Respondent. ) ADA-DTG\n )\n\n\n DECLARATION OF JORDAN R. JAFFE IN SUPPORT OF RESPONDENT\u2019S\n MEMORANDUM IN RESPONSE TO PETITIONER\u2019S MOTION TO COMPEL\n COMPLIANCE WITH SUBPOENAS SERVED ON NON-PARTY GOOGLE LLC\n\f Case 7:26-mc-00324-LS Document 7-1 Filed 08/25/26 Page 2 of 5\n\n\n\n\n I, Jordan R. Jaffe, declare on personal knowledge as follows:\n\n 1. I am an attorney at Wilson Sonsini Goodrich & Rosati, P.C., counsel for Google\n\nLLC (\u201cGoogle\u201d) in this matter. This declaration is based on personal knowledge and if called, I\n\ncould and would testify competently to the facts herein.\n\n 2. Since Neural AI, LLC (\u201cNeural\u201d) issued its third-party subpoena to Google, I\n\nhave been involved in each meet-and-confer between the parties.\n\n 3. Attached as Exhibit A is a true and correct copy of the parties\u2019 email\n\ncommunications related to the subpoenas.\n\n 4. Attached as Exhibit B are excerpts from Form 10-K filed by Alphabet Inc. with\n\nthe U.S. Securities and Exchange Commission (\u201cSEC\u201d).1\n\n 5. According to Ex. B, Alphabet Inc. had 190,820 employees as of December 31,\n\n2025. Ex. B at 13. Google is Alphabet\u2019s largest business, id. at 50, and includes business\n\nsegments that include Google Services and Google Cloud, id. at 7. \u201cGoogle Services\u2019 core\n\nproducts and platforms include ads, Android, Chrome, devices, Gmail, Google Drive, Google\n\nGemini, Google Maps, Google Photos, Google Play, Search, and YouTube.\u201d Id. at 7\u20138.\n\n 6. According to Ex. B, \u201c[a]t the foundation of [Google\u2019s]w full-stack approach is our\n\nAI-optimized infrastructure\u2014a key differentiator enabling us to power our own products, such as\n\nSearch and YouTube, and support the services we provide to our Google Cloud customers.\u201d Id.\n\nat 7. This \u201ctechnical infrastructure allows us to use and offer our customers a range of AI\n\naccelerator options, including specialized Graphics Processing Units (GPUs) and our own\n\ncustom-built Tensor Processing Units (TPUs), such as Ironwood, our seventh-generation TPU.\u201d\n\n\n1\n The full Form 10-K is available at:\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm.\n\n\n 1\n\f Case 7:26-mc-00324-LS Document 7-1 Filed 08/25/26 Page 3 of 5\n\n\n\n\nId. at 7. This further includes \u201cworld-class research, including models and tooling; and [its]\n\nproducts and platforms that bring AI to billions of people, developers, and enterprises,\u201d id.\n\nGoogle\u2019s \u201cAI-optimized infrastructure\u201d enabled Google to embed \u201cthe power of generative AI\n\nand Gemini into [its] products and platforms.\u201d Id. For example, Google provides \u201cAI\n\nOverviews\u201d and \u201cAI Mode in Search\u201d along with \u201centerprise AI solutions on [its] Google Cloud\n\nPlatform,\u201d id. at 50, which includes the Vertex AI platform and Gemini Enterprise, id. at 54.\n\n 7. According to Ex. B, Google invests large sums in capital expenditure as it scales\n\nits infrastructure, expending $91.4 billion in 2025, which was up from $52.5 billion in 2024. Id.\n\nat 68. This included investments in \u201cservers and network equipment, and data centers.\u201d Id\n\n 8. Neural\u2019s Subpoenas include a definition for \u201cNVIDIA GPUs\u201d that lists\n\napproximately 240 products. See, e.g., Dkt. 1-6 at 6\u20138. As described above, Google broadly\n\nuses AI and has vast amounts of AI technical infrastructure. As also described above, Google\n\nuses AI across many products and features at Google. Based on that information, tracking down\n\neach of the requested \u201cNVIDIA GPUs\u201d across all Google products and services, determining\n\nhow each GPU is used, and how each GPU and associated software are configured, would be\n\nunduly burdensome, if not impossible. This would further require consulting any number of\n\nthousands of Google employees and related documentation regarding their use of AI\n\ninfrastructure, which would likely take months, if not longer. See supra \u00b6\u00b6 5\u20136. Further, even\n\nafter identifying the requested \u201cNVIDIA GPUs,\u201d cataloguing this information would require the\n\ncollection and production of voluminous records, adding to the unduly burdensome requests.\n\n\n\n\n 2\n\f Case 7:26-mc-00324-LS Document 7-1 Filed 08/25/26 Page 4 of 5\n\n\n\n\n I declare under penalty of perjury under the laws of the United States of America that\n\nthe foregoing is true and correct.\n\n Executed on August 25, 2026, at Pittsburgh, Pennsylvania.\n\n\n\n /s/ Jordan R. Jaffe\n\n Jordan R. Jaffe\n\n\n\n\n 3\n\f Case 7:26-mc-00324-LS Document 7-1 Filed 08/25/26 Page 5 of 5\n\n\n\n\n CERTIFICATE OF SERVICE\n\n The undersigned certifies that, on August 25, 2026, all counsel of record are being served\n\nwith a copy of this document and exhibits attached hereto via CM/ECF to the following:\n\n Susman Godfrey\n\n Brian D. Melton\n 1000 Louisiana St.\n Suite 5100\n Houston, TX 77002\n bmelton@susmangodfrey.com\n\n Max L. Tribble , Jr.\n 1000 Louisiana\n Suite 5100\n Houston, TX 77002-5096\n mtribble@susmangodfrey.com\n 713-653-7820\n\n Rocco Magni\n 1000 Louisiana, Suite 5100\n Houston, TX 77002-5096\n rmagni@susmangodfrey.com\n\n Tanner H. Laiche\n 401 Union St., Suite 3000\n Seattle, WA 98101\n tlaiche@susmangodfrey.com\n 206-516-3880\n\n Attorneys for Petitioner Neural AI, LLC\n\n /s/ Jason M. Storck\n Jason M. Storck\n\n\n\n\n 4\n\f","ocr_status":1,"date_upload":"2026-08-26T06:58:14.227209-07:00","document_number":"7","attachment_number":1,"pacer_doc_id":"181037269165","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Declaration of Jordan R. Jaffe","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/491364354/","id":491364354,"tags":[],"absolute_url":"/docket/74667129/7/2/neural-ai-llc-v-google-inc/","date_created":"2026-08-26T06:55:31.816966-07:00","date_modified":"2026-09-08T10:54:16.820814-07:00","sha1":"7427ad3e50a8d1d58d7ca44623a7432f95c5598b","page_count":17,"file_size":1117544,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.7.2.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.7.2.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"","ocr_status":null,"date_upload":"2026-08-26T06:58:16.126330-07:00","document_number":"7","attachment_number":2,"pacer_doc_id":"181037269166","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit A to Jaffe Decl - Email Chain re Subpoena","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/491364355/","id":491364355,"tags":[],"absolute_url":"/docket/74667129/7/3/neural-ai-llc-v-google-inc/","date_created":"2026-08-26T06:55:31.828966-07:00","date_modified":"2026-09-28T09:37:19.540378-07:00","sha1":"a087830adc85ee243d773ddd3951b79fd0fb94c6","page_count":19,"file_size":636930,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.7.3.pdf","filepath_ia":"","ia_upload_failure_count":3,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-LS Document 7-3 Filed 08/25/26 Page 1 of 19\n\n\n\n\n EXHIBIT B\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 2 of 19\n\n\n\n\n UNITED STATES\n SECURITIES AND EXCHANGE COMMISSION\n Washington, D.C. 20549\n ___________________________________________\n\n\n\n\n FORM 10-K\n ___________________________________________\n\n (Mark One)\n \u2612 ANNUAL REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934\n For the fiscal year ended December 31, 2025\n OR\n \u2610 TRANSITION REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934\n For the transition period from to .\n Commission file number: 001-37580\n ___________________________________________\n\n\n Alphabet Inc.\n (Exact name of registrant as specified in its charter)\n ___________________________________________\n Delaware XX-XXXXXXX\n (State or other jurisdiction of incorporation or organization) (I.R.S. Employer Identification No.)\n 1600 Amphitheatre Parkway\n Mountain View, CA 94043\n (Address of principal executive offices, including zip code)\n (650) 253-0000\n (Registrant's telephone number, including area code)\n Securities registered pursuant to Section 12(b) of the Act:\n Title of each class Trading Symbol(s) Name of each exchange on which registered\n Class A Common Stock, $0.001 par value GOOGL Nasdaq Stock Market LLC\n (Nasdaq Global Select Market)\n Class C Capital Stock, $0.001 par value GOOG Nasdaq Stock Market LLC\n (Nasdaq Global Select Market)\n 2.375% Senior Notes due 2028 \u2014 Nasdaq Stock Market LLC\n 2.500% Senior Notes due 2029 \u2014 Nasdaq Stock Market LLC\n 2.875% Senior Notes due 2031 \u2014 Nasdaq Stock Market LLC\n 3.000% Senior Notes due 2033 \u2014 Nasdaq Stock Market LLC\n 3.125% Senior Notes due 2034 \u2014 Nasdaq Stock Market LLC\n 3.375% Senior Notes due 2037 \u2014 Nasdaq Stock Market LLC\n 3.500% Senior Notes due 2038 \u2014 Nasdaq Stock Market LLC\n 4.000% Senior Notes due 2044 \u2014 Nasdaq Stock Market LLC\n 3.875% Senior Notes due 2045 \u2014 Nasdaq Stock Market LLC\n 4.000% Senior Notes due 2054 \u2014 Nasdaq Stock Market LLC\n 4.375% Senior Notes due 2064 \u2014 Nasdaq Stock Market LLC\n Securities registered pursuant to Section 12(g) of the Act:\n Title of each class\n None\n ___________________________________________\n\n Indicate by check mark if the registrant is a well-known seasoned issuer, as defined in Rule 405 of the Securities Act. Yes \u2612 No \u2610\n Indicate by check mark if the registrant is not required to file reports pursuant to Section 13 or Section 15(d) of the Act. Yes \u2610 No \u2612\n\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 1/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 3 of 19\n Table of Contents Alphabet Inc.\n\n\n\n\n Making AI Helpful for Everyone\n We believe AI is a profound platform shift that can bring meaningful and positive change to people and societies\n across the world, and to our business. We aim to build the most advanced, safe, and responsible AI through our full-stack\n approach, which spans AI-optimized infrastructure; world-class research, including models and tooling; and our products\n and platforms that bring AI to billions of people, developers, and enterprises.\n At the foundation of our full-stack approach is our AI-optimized infrastructure \u2014 a key differentiator enabling us to\n power our own products, such as Search and YouTube, and support the services we provide to our Google Cloud\n customers. Our technical infrastructure allows us to use and offer our customers a range of AI accelerator options,\n including specialized Graphics Processing Units (GPUs) and our own custom-built Tensor Processing Units (TPUs), such\n as Ironwood, our seventh-generation TPU. We are focused on driving efficiencies in our data centers, allowing us to\n leverage our technical infrastructure to deliver our products and services at an increasing scale while simultaneously\n enabling world-class research and model development.\n Over the last decade, our research teams have pushed the boundaries of AI forward, which is displayed through\n Gemini 3, our most intelligent AI model yet. Designed to deliver advanced multimodal understanding, Gemini 3 represents\n our most capable iteration of agentic and generative coding technologies. Gemini 3 integrates enhanced reasoning\n capabilities to support visualizations and interactive user experiences across our product ecosystem, including Search and\n the Gemini app.\n As technology continues to improve rapidly, we are focused on bringing our latest AI advances to our products and\n platforms. We continue to help our users access information and knowledge, express themselves, and get things done by\n embedding the power of generative AI and Gemini into our products and platforms. Today, all 15 of our half-billion-user\n products \u2014 including seven with two billion users \u2014 use our Gemini models. For our Google Cloud customers, our\n offerings are helping organizations stay at the forefront of innovation with solutions such as Gemini Enterprise and Gemini\n for Google Workspace.\n Guided by our AI principles, we believe our approach to AI must be both bold and responsible. That means\n developing AI in a way that maximizes the positive benefits to society while addressing its potential challenges.\n Moonshots\n Many companies get comfortable doing what they have always done, making only incremental changes. This\n incrementalism leads to irrelevance over time, especially in technology, where change tends to be revolutionary, not\n evolutionary.\n Our early investments in AI started out as moonshots but are now incorporated into our core products and central to\n future developments. In Other Bets, our fully autonomous driving technology company, Waymo, is now providing fully\n autonomous, paid ride-hailing services to customers in multiple cities. Isomorphic Labs is reimagining the drug discovery\n process from first principles, applying AI to accelerate the development of new medicines. We continue to look toward the\n future and to invest for the long term, most notably for the application of AI to our products and services, as well as other\n frontier technologies such as quantum computing.\n Privacy and Security\n We make it a priority to protect the privacy and security of our products, users, and customers, even if there are near-\n term financial consequences. We do this by continuously investing in building products that are secure by default; strictly\n upholding responsible data practices that emphasize privacy by design; and building easy-to-use settings that put people\n in control. We are continually enhancing these efforts over time, whether by enabling users to auto-delete their data,\n applying privacy technologies like on-device processing, giving people tools to control their experience, or advancing anti-\n malware, anti-phishing, and password security features.\n Google\n For reporting purposes Google comprises two segments: Google Services and Google Cloud.\n Google Services\n Serving Our Users\n We have always been committed to building helpful products that can improve the lives of millions of people\n worldwide. Our product innovations are what make our services widely used, and our brand one of the most recognized in\n the world. Google Services' core products and platforms include ads, Android, Chrome, devices, Gmail, Google Drive,\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 7/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 4 of 19\n Google Gemini, Google Maps, Google Photos, Google Play, Search, and YouTube, with broad and growing adoption by\n users around the world.\n\n\n\n 4.\n\n\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 8/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 5 of 19\n Table of Contents Alphabet Inc.\n\n\n\n Our products and services have come a long way since the company was founded more than 25 years ago. While\n Google Search started as a way to find web pages, organized into ten blue links, we have driven technical advancements\n and product innovations that have transformed Google Search into a dynamic, multimodal experience. Large language\n models have made it possible to express more natural language queries, vastly improving the types of questions users can\n ask, and the quality of results. For example, AI Overviews makes it easier to ask Google anything and get a helpful\n response. AI Mode allows users to ask more nuanced questions that might have previously taken multiple searches, using\n Gemini\u2019s advanced reasoning, thinking, and multimodal capabilities.\n This drive to make information more accessible and helpful has led us over the years to improve the discovery and\n creation of digital content both on the web and through platforms like Google Play and YouTube. People are consuming\n many forms of digital content, including watching long and short form videos and podcasts, streaming TV, playing games,\n listening to music, reading books, and using apps. Working with content creators and partners, we continue to build new\n ways for people around the world to create and find great digital content.\n Fueling all of these great digital experiences are extraordinary platforms and devices. That is why we continue to\n invest in platforms like our Android mobile operating system, Chrome browser, and Chrome operating system, as well as\n our family of devices. We see tremendous potential for devices to be helpful and make people's lives easier by combining\n the best of our AI, software, and hardware. This potential is reflected in our latest generation of devices, such as the new\n Pixel 10 series and the Pixel Watch 4. Creating products and services that people rely on every day is a journey that we\n are investing in for the long-term.\n How We Make Money\n We have built world-class advertising technologies for advertisers, agencies, and publishers to power their digital\n marketing businesses. Our advertising solutions help millions of companies grow their businesses through our wide range\n of products across devices and formats, and we aim to ensure positive user experiences by serving the right ads at the\n right time and by building deep partnerships with brands and agencies. AI has been foundational to our advertising\n business for more than a decade. Products like Demand Gen, Performance Max, and Product Studio use the full power of\n our AI to help advertisers find untapped and incremental conversion opportunities.\n Google Services generates revenues primarily by delivering both performance and brand advertising that appears on\n Google Search & other properties, YouTube, and Google Network partners' properties (\"Google Network properties\"). We\n continue to invest in both performance and brand advertising and seek to improve the measurability of advertising so\n advertisers understand the effectiveness of their campaigns.\n \u2022 Performance advertising creates and delivers relevant ads that users will click on leading to direct engagement\n with advertisers. Performance advertising lets our advertisers connect with users while driving measurable results.\n Our ads tools allow performance advertisers to create simple text-based ads.\n \u2022 Brand advertising helps enhance users' awareness of and affinity for advertisers' products and services, through\n videos, text, images, and other interactive ads that run across various devices. We help brand advertisers deliver\n digital videos and other types of ads to specific audiences for their brand-building marketing campaigns.\n We have allocated substantial resources to stopping bad advertising practices and protecting users on the web. We\n focus on creating the best advertising experiences for our users and advertisers in many ways, including filtering out invalid\n traffic, removing billions of bad ads from our systems every year, and closely monitoring the sites, apps, and videos where\n ads appear and blocklisting them when necessary to ensure that ads do not fund bad content.\n In addition, Google Services generates revenues from products and services beyond advertising, including:\n \u2022 consumer subscriptions, which primarily include revenues from YouTube services, such as YouTube TV,\n YouTube Music and Premium, and NFL Sunday Ticket, as well as Google One, which offers access to our most\n capable Gemini models;\n \u2022 platforms, which primarily include revenues from Google Play sales of apps and in-app purchases; and\n \u2022 devices, which primarily include sales of the Pixel family of devices.\n Google Cloud\n Through our Google Cloud Platform and Google Workspace offerings, Google Cloud generates revenues primarily\n from consumption-based fees and subscriptions for infrastructure, platform, applications, and other cloud services.\n Customers use Google Cloud in multiple ways such as:\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 9/156\n\f8/24/26,\n8/24/26, 8:46\n 8:46 PM\n PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26\n goog-20251231 Page 6 of 19\n\n 5.\n\n\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 10/156\n 10/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 7 of 19\n Table of Contents Alphabet Inc.\n\n\n\n\n \u2022 AI-optimized Infrastructure: runs on our Cloud, at the edge, or in customers' data centers. It can be used to\n migrate and modernize information technology (IT) systems and to train and serve various types of AI models. Our\n AI infrastructure delivers cost-performance for AI workloads. We offer a range of AI accelerators, including our\n custom TPUs and specialized GPUs, as well as AI-optimized storage offerings, and efficient AI software.\n \u2022 Developer Platform: delivers a fully managed AI development platform, through Vertex AI, for accessing, tuning,\n augmenting, and deploying custom models and agents, helping customers build applications with more than 200\n foundation models, including our Gemini family, third-party, and open models.\n \u2022 Cybersecurity: provides AI-powered threat intelligence and cybersecurity solutions to help customers detect,\n analyze, protect against, and respond to a broad range of cybersecurity threats.\n \u2022 Data and Analytics: enables customers to migrate, clean, prepare, and feed data into their models. Our data\n platform also unifies data lakes, data warehouses, data governance, and advanced machine learning into a single\n platform that helps users analyze data using AI models across any cloud.\n \u2022 Agents:\n \u25e6 Gemini Enterprise: empowers teams to discover, create, share, and run AI agents all in one secure\n platform, bringing the best of Google AI to employees through an intuitive chat interface, helping to\n automate workflows and drive smarter business outcomes.\n\n \u25e6 Gemini for Google Workspace: brings our AI-powered agents into Gmail, Docs, Sheets, and more to help\n users write, organize, visualize, accelerate workflows, and have more productive meetings.\n Other Bets\n Across Alphabet, we are also using technology to try to solve big problems that affect a wide variety of industries,\n including transportation and health technology. Alphabet\u2019s investment in the portfolio of Other Bets includes businesses\n that are at various stages of development, ranging from those in the research and development phase, such as X, our\n moonshot factory focused on developing breakthrough technologies, to those that are scaling commercialization, such as\n Waymo, which is expanding to more cities domestically, entering international markets, and further scaling operations.\n Other Bets operate as independent companies and some of them have their own boards with independent members\n and outside investors. While these early-stage businesses naturally come with considerable uncertainty, some of them are\n already generating revenue and making important strides in their industries. Revenues from Other Bets are generated\n primarily from the sale of autonomous transportation and internet services.\n Competition\n Our business is characterized by rapid change as well as new and disruptive technologies. We face formidable\n competition in every aspect of our business, including but not limited to, from:\n \u2022 general purpose search engines and information services;\n \u2022 vertical search engines and e-commerce providers for queries on topics such as those related to travel, jobs, and\n health, which users may navigate directly to rather than go through Google;\n \u2022 online advertising platforms and networks, including online shopping and streaming services;\n \u2022 other forms of advertising, such as billboards, magazines, newspapers, radio, and television, as our advertisers\n typically advertise in multiple media, both online and offline;\n \u2022 digital content and application platform providers;\n \u2022 providers of enterprise cloud services;\n \u2022 AI model developers and providers of AI products and services;\n \u2022 companies that design, manufacture, and market consumer hardware products, including businesses that have\n developed proprietary platforms;\n \u2022 providers of digital video services;\n \u2022 social networks, which users may rely on for product or service referrals, rather than seeking information through\n traditional search engines; and\n \u2022 providers of workspace communication and connectivity products.\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 11/156\n\f8/24/26,\n8/24/26, 8:46\n 8:46 PM\n PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26\n goog-20251231 Page 8 of 19\n\n\n 6.\n\n\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 12/156\n 12/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 9 of 19\n Table of Contents Alphabet Inc.\n\n\n\n\n Competing successfully depends heavily on our ability to continually develop and distribute innovative products and\n technologies to the marketplace across our businesses. For example, for advertising, competing successfully depends on\n attracting and retaining:\n \u2022 users, for whom other products and services are literally one click away, on the basis of the relevance of our\n advertising, as well as the general usefulness, security, and availability of our products and services;\n \u2022 advertisers, primarily based on our ability to generate sales leads, and ultimately customers, and to deliver their\n advertisements in an efficient and effective manner across a variety of distribution channels even as trends in\n advertising mediums and user preferences change; and\n \u2022 content providers, primarily based on the quality of our advertiser base, our ability to help these partners generate\n revenues from advertising, and the terms of our agreements with them.\n For additional information about competition, see Item 1A Risk Factors of this Annual Report on Form 10-K.\n Culture and Workforce\n Our people are critical for our continued success, so we work hard to create an environment where employees can\n have fulfilling careers and perform at a high level. We offer industry-leading benefits and programs to take care of the\n diverse needs of our employees and their families, including opportunities for career growth and development, resources to\n support their financial health, and access to excellent healthcare choices. Our competitive compensation programs help us\n to attract and retain key talent, and we will continue to invest in recruiting talented people to technical and non-technical\n roles and rewarding them well. We provide a variety of high-quality training and support to managers to build and\n strengthen their capabilities \u2014 ranging from courses for new managers, to learning resources that help them provide\n feedback and manage performance, to coaching and individual support.\n As of December 31, 2025, Alphabet had 190,820 employees. We have work councils and statutory employee\n representation obligations in certain countries, and we are committed to supporting protected labor rights, maintaining an\n open culture, and listening to our employees.\n When appropriate we partner with outside companies on a contractual basis to provide a specialized service or to\n temporarily cover a short-term need. The employees of our suppliers and staffing partners \u2014 vendors and temporary staff,\n respectively \u2014 and independent contractors who are self-employed, make up our extended workforce. We choose our\n partners and staffing agencies carefully, and review their compliance with Google\u2019s Supplier Code of Conduct.\n Government Regulation\n We are subject to numerous United States (US) federal, state, and local, as well as foreign laws, and regulations\n covering a wide variety of subjects, and the scope of this coverage continues to broaden with continuing new legal and\n regulatory developments in the US and internationally. Like other companies in the technology industry, we face\n increasingly heightened scrutiny from both US and foreign governments with respect to our compliance with laws and\n regulations. Many of these laws and regulations are evolving and their applicability and scope, as interpreted by the courts,\n remain uncertain. Particularly with regard to AI; competition; consumer protection; content moderation, including access\n restrictions for minors; data privacy and security; intellectual property; news publications; and sustainability and other\n social matters, we have seen an increase in new and evolving laws and regulations, as well as related enforcement actions\n and investigations, being proposed and implemented in recent years by legislative and regulatory bodies around the world.\n As we have seen in recent years, different laws and regulations on the same topic may not always have the same\n requirements (and sometimes may seem to have conflicting requirements), and even when requirements overlap, the rules\n are not always consistently implemented, interpreted, and enforced from jurisdiction to jurisdiction.\n Our compliance with these laws and regulations may be onerous and could, individually or in the aggregate, increase\n our cost of doing business, make our products and services less useful, limit our ability to pursue certain business\n practices or offer certain products and services (either in certain geographies or at all), cause us to change our business\n models and operations, affect our competitive position relative to our peers, or otherwise harm our business, reputation,\n financial condition, and operating results.\n For additional information about government regulation applicable to our business, see Item 1A Risk Factors; Trends\n in Our Business and Financial Effect in Part II, Item 7; and Legal Matters in Note 10 of the Notes to Consolidated Financial\n Statements included in Part II, Item 8 of this Annual Report on Form 10-K.\n\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 13/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 10 of 19\n Table of Contents Alphabet Inc.\n\n\n\n\n ITEM 7. MANAGEMENT\u2019S DISCUSSION AND ANALYSIS OF FINANCIAL CONDITION AND RESULTS OF\n OPERATIONS\n Please read the following discussion and analysis of our financial condition and results of operations together with\n \u201cNote about Forward-Looking Statements,\u201d Part I, Item 1 \"Business,\" Part I, Item 1A \"Risk Factors,\" and our consolidated\n financial statements and related notes included under Item 8 of this Annual Report on Form 10-K.\n The following section generally discusses 2025 results compared to 2024 results. Discussion of 2024 results\n compared to 2023 results to the extent not included in this report can be found in Item 7 of our 2024 Annual Report on\n Form 10-K.\n Understanding Alphabet\u2019s Financial Results\n Alphabet is a collection of businesses \u2014 the largest of which is Google. We report Google in two segments, Google\n Services and Google Cloud, and all non-Google businesses collectively as Other Bets. Supporting these businesses, we\n have centralized certain AI-related research and development focused on advanced research in AI and developing the\n frontier models that serve our businesses, which is reported in Alphabet-level activities. For further details on our\n segments, see Part I, Item 1 Business and Note 15 of the Notes to Consolidated Financial Statements included in Item 8 of\n this Annual Report on Form 10-K.\n Trends in Our Business and Financial Effect\n The following long-term trends have contributed to the results of our consolidated operations, and we anticipate that\n they will continue to affect our future results:\n \u2022 As we continue to grow our business and meet the evolving behaviors and needs of our users and\n customers, our revenue growth and mix along with our cost and margin profiles are being influenced by a number\n of factors, including:\n Expanded AI Offerings in our Products and Services: The continuing evolution of the online world has contributed\n to the growth of our business. We expect that this evolution, including user engagement with AI products and\n services, will continue to benefit our business and our revenues. As we continue to incorporate AI into our products\n and services, such as with AI Overviews and AI Mode in Search, and with enterprise AI solutions on our Google Cloud\n Platform, we may monetize differently than our historical consumer and enterprise offerings which could affect\n revenue growth rates and margin trends. When developing new products and services we generally focus first on\n user experience and then on monetization. At the same time, we face increasing competition, including from other\n developers and providers of AI products and services, which may affect our revenues.\n Increasing Revenues Beyond Advertising: Revenues from cloud, consumer subscriptions, platforms, and devices,\n which may have differing characteristics than our advertising revenues, have grown over time. Certain of these\n revenues have been growing at a rate higher than our advertising revenues, becoming a larger percentage of our\n consolidated revenues, and we expect this trend to continue. The margins on these revenues vary significantly and\n are generally lower than the margins on our advertising revenues.\n Increased Investment in Technical Infrastructure: We continue to invest in capital expenditures as we scale our\n technical infrastructure, in particular for AI, to meet the demand of our users and enterprise customers and to support\n research internally. We invested heavily in capital expenditures in 2025 and in 2026, we expect to significantly\n increase, relative to 2025, our investment in our technical infrastructure, including servers and network equipment,\n and data centers. The costs associated with operating our technical infrastructure - depreciation, energy, equipment,\n and network capacity - are expected to significantly increase as developing and serving AI offerings require more\n compute power than our historical consumer and enterprise offerings. While our technical infrastructure costs\n increase, we expect to continue to drive efficiencies in our data centers, for example, through the design of our AI\n models and our TPU and GPU-based technical infrastructure.\n Continued Investment in Intellectual Property through R&D and Acquisitions: We continue to make significant\n research and development investments in areas of strategic focus as we seek to develop new, innovative offerings,\n and improve our existing offerings across our businesses. Acquisitions and strategic investments remain important\n elements in our use of capital and contribute to the breadth and depth of our offerings, expand our expertise in\n engineering and other functional areas, and build strong partnerships around strategic initiatives.\n Traffic Acquisition Costs Growth and Rate Changes: We expect traffic acquisition costs (\"TAC\") paid to our\n distribution partners and Google Network partners to increase as our advertising revenues grow. Our overall TAC as a\n percentage of our advertising revenues (\"TAC rate\") has been decreasing primarily due to a revenue mix\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 50/156\n\f8/24/26,\n8/24/26, 8:46\n 8:46 PM\n PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26\n goog-20251231 Page 11 of 19\n\n\n 28.\n 28.\n\n\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 51/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 12 of 19\n Table of Contents Alphabet Inc.\n\n\n\n\n shift from Google Network properties to Google Search & other properties. Our TAC rate will continue to be affected\n by changes in device mix; geographic mix; partner agreement terms; partner mix; the percentage of queries\n channeled through paid access points; product mix; the relative revenue growth rates of advertising revenues from\n different channels; and revenue share terms.\n \u2022 We have raised capital through external financing in the form of debt and we may continue to seek debt or\n other forms of financing in the future to support our capital and operating needs.\n In 2025, we raised capital through the issuance of debt and we expect to continue to assess the use of debt and other\n forms of financing in the future. We expect to continue to enter into finance leases, primarily for data centers. Additionally,\n in 2025, we provided credit support, such as through backstops and guarantees, to certain infrastructure related\n counterparties and may continue to provide additional credit support in the future.\n \u2022 We face an evolving regulatory environment, and we are subject to claims, lawsuits, investigations, and\n other forms of potential legal liability, which could affect our business practices and financial results.\n Changes in social, political, economic, tax, and regulatory conditions or in laws and policies governing a wide range of\n topics and related legal matters, including investigations, lawsuits, and regulatory actions, have resulted in fines and\n caused us to change our business practices. As the regulatory environment continues to evolve, we may continue to incur\n fines and we expect increased costs associated with compliance, modifications to our products and services, and\n limitations on our ability to pursue certain business practices. For additional information, see Part I, Item 1A Risk Factors\n and Legal Matters in Note 10 of the Notes to Consolidated Financial Statements included in Item 8 of this Annual Report\n on Form 10-K.\n Revenues and Monetization Metrics\n We generate revenues by delivering relevant, cost-effective online advertising; cloud-based solutions that provide\n enterprise customers of all sizes with infrastructure, platform services, and applications; and sales of other products and\n services, such as fees received for subscription-based products, apps and in-app purchases, and devices. For additional\n information on how we recognize revenue, see Note 1 of the Notes to Consolidated Financial Statements included in Item\n 8 of this Annual Report on Form 10-K.\n In addition to the long-term trends and their financial effect on our business discussed above, fluctuations in our\n revenues have been and may continue to be affected by a combination of factors, including:\n \u2022 changes in foreign currency exchange rates;\n \u2022 changes in pricing, such as those resulting from changes in fee structures, discounts, and customer incentives;\n \u2022 general economic conditions and various external dynamics, including geopolitical events, regulations, and other\n measures and their effect on advertiser, consumer, and enterprise spending;\n \u2022 new product, service, and market launches; and\n \u2022 seasonality.\n Additionally, fluctuations in our revenues generated from advertising (\"Google advertising\"), other sources (\"Google\n subscriptions, platforms, and devices\"), Google Cloud, and Other Bets have been, and may continue to be, affected by\n other factors unique to each set of revenues, as described below.\n Google Services\n Google Services revenues consist of Google advertising as well as Google subscriptions, platforms, and devices\n revenues.\n Google Advertising\n Google advertising revenues are comprised of the following:\n \u2022 Google Search & other, which includes revenues generated on Google search properties (including revenues from\n traffic generated by search distribution partners who use Google.com as their default search in browsers, toolbars,\n etc.), and other Google owned and operated properties like Gmail, Google Maps, and Google Play;\n \u2022 YouTube ads, which includes revenues generated on YouTube properties; and\n\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 52/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 13 of 19\n \u2022 Google Network, which includes revenues generated on Google Network properties participating in AdMob,\n AdSense, and Google Ad Manager.\n\n\n\n 29.\n\n\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 53/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 14 of 19\n Table of Contents Alphabet Inc.\n\n\n\n\n We use certain metrics to track how well traffic across various properties is monetized as it relates to our advertising\n revenues: paid clicks and cost-per-click pertain to traffic on Google Search & other properties, while impressions and cost-\n per-impression pertain to traffic on our Google Network properties.\n Paid clicks represent engagement by users and include clicks on advertisements by end-users on Google search\n properties and other Google owned and operated properties including Gmail, Google Maps, and Google Play. Cost-per-\n click is defined as click-driven revenues divided by our total number of paid clicks and represents the average amount we\n charge advertisers for each engagement by users.\n Impressions include impressions displayed to users on Google Network properties participating primarily in AdMob,\n AdSense, and Google Ad Manager. Cost-per-impression is defined as impression-based and click-based revenues divided\n by our total number of impressions, and represents the average amount we charge advertisers for each impression\n displayed to users.\n As our business evolves, we periodically review, refine, and update our methodologies for monitoring, gathering, and\n counting the number of paid clicks and the number of impressions, and for identifying the revenues generated by the\n corresponding click and impression activity.\n Fluctuations in our advertising revenues, as well as the change in paid clicks and cost-per-click on Google Search &\n other properties and the change in impressions and cost-per-impression on Google Network properties and the correlation\n between these items have been, and may continue to be, affected by factors in addition to the general factors described\n above, such as:\n \u2022 advertiser competition for keywords;\n \u2022 changes in advertising quality, formats, delivery, or policy;\n \u2022 changes in device mix;\n \u2022 seasonal fluctuations in internet usage, advertising expenditures, and underlying business trends, such as\n traditional retail seasonality; and\n \u2022 traffic growth in emerging markets compared to more mature markets and across various verticals and channels.\n Google Subscriptions, Platforms, and Devices\n Google subscriptions, platforms, and devices revenues are comprised of the following:\n \u2022 consumer subscriptions, which primarily include revenues from YouTube services, such as YouTube TV, YouTube\n Music and Premium, and NFL Sunday Ticket, as well as Google One, which offers access to our most capable\n Gemini models;\n \u2022 platforms, which primarily include revenues from Google Play sales of apps and in-app purchases;\n \u2022 devices, which primarily include sales of the Pixel family of devices; and\n \u2022 other products and services.\n Fluctuations in our Google subscriptions, platforms, and devices revenues have been, and may continue to be,\n affected by factors in addition to the general factors described above, such as changes in customer usage and demand,\n number of subscribers, and the timing of product launches.\n Google Cloud\n Google Cloud revenues are comprised of the following:\n \u2022 Google Cloud Platform primarily generates consumption-based fees and subscriptions for infrastructure, platform,\n and other services. These services provide access to solutions such as AI offerings including our enterprise AI\n infrastructure, Vertex AI platform, and Gemini Enterprise; cybersecurity offerings; and data and analytics solutions;\n \u2022 Google Workspace includes subscriptions for cloud-based communication and collaboration tools for enterprises,\n such as Gmail, Docs, Calendar, Drive, and Meet, with integrated features like Gemini for Google Workspace; and\n \u2022 other enterprise services.\n Fluctuations in our Google Cloud revenues have been, and may continue to be, affected by factors in addition to the\n general factors described above, such as changes in customer usage, demand, and supply availability.\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 54/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 15 of 19\n Table of Contents Alphabet Inc.\n\n\n\n\n Net cash provided by operating activities increased from 2024 to 2025 due to an increase in cash received from\n customers, partially offset by an increase in cash payments for cost of revenues and operating expenses.\n Cash Used in Investing Activities\n Cash provided by investing activities consists primarily of maturities and sales of investments in marketable and non-\n marketable securities. Cash used in investing activities consists primarily of purchases of marketable and non-marketable\n securities, purchases of property and equipment, and payments for acquisitions.\n Net cash used in investing activities increased from 2024 to 2025, primarily due to an increase in purchases of\n property and equipment, driven by investments in technical infrastructure, and a decrease in maturities and sales of\n marketable securities.\n Cash Used in Financing Activities\n Cash provided by financing activities consists primarily of proceeds from issuance of debt and proceeds from the sale\n of interests in consolidated entities. Cash used in financing activities consists primarily of repurchases of stock,\n repayments of debt, net payments related to stock-based award activities, and dividend payments.\n Net cash used in financing activities decreased from 2024 to 2025 due to an increase in proceeds from issuance of\n debt and a decrease in repurchases of stock, partially offset by repayments of debt.\n Liquidity and Material Cash Requirements\n We expect existing cash, cash equivalents, short-term marketable securities, and cash flows from operations and\n financing activities to continue to be sufficient to fund our operating activities and cash commitments for investing and\n financing activities for at least the next 12 months, and thereafter for the foreseeable future.\n Capital Expenditures and Leases\n We make investments in land, buildings, and servers and network equipment through purchases of property and\n equipment and lease arrangements to provide capacity for the growth of our services and products.\n Capital Expenditures\n Our capital investments in property and equipment consist primarily of the following major categories:\n \u2022 technical infrastructure, which consists of our investments in servers and network equipment, data center land, and\n building construction and improvements; and\n \u2022 office facilities, ground-up development projects, and building improvements.\n Assets not yet in service are those that are not ready for their intended use, including assets in the process of\n construction or assembly, and consist primarily of technical infrastructure. The time frame from date of purchase to\n placement in service of these assets may extend from months to years. For example, our data center construction projects\n are generally multi-year projects with multiple phases, where we acquire land and buildings, construct buildings, and\n secure and install servers and network equipment.\n During the years ended December 31, 2024 and 2025, we spent $52.5 billion and $91.4 billion on capital\n expenditures, respectively. In 2026, we expect to significantly increase, relative to 2025, our investment in our technical\n infrastructure, including servers and network equipment, and data centers. Depreciation of our property and equipment\n commences when such assets are ready for their intended use. For the years ended December 31, 2024 and 2025, our\n depreciation on property and equipment was $15.3 billion and $21.1 billion, respectively.\n Leases\n As of December 31, 2025, the amount of total undiscounted future lease payments under operating leases was $18.3\n billion, of which $3.3 billion is short-term, and total undiscounted future lease payments under finance leases was $2.9\n billion, of which $491 million is short-term.\n As of December 31, 2025, we have entered into leases primarily related to data centers that have not yet commenced\n with short-term and long-term future lease payments of $5.8 billion and $52.7 billion, respectively. These leases will\n commence between 2026 and 2031 with non-cancelable lease terms primarily between one and 25 years.\n In January 2026, we executed a power purchase agreement which we expect to be accounted for as a lease resulting\n in future payments depending on certain agreement terms of $9.9 billion between 2027 and 2047. If certain contractual\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 68/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 16 of 19\n conditions for the project are not met, we would instead make a one-time payment of approximately $3.5 billion and\n assume ownership of the power generating assets.\n\n\n\n 38.\n\n\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 69/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 17 of 19\n Table of Contents Alphabet Inc.\n\n\n\n\n For additional information on leases, see Note 4 of the Notes to Consolidated Financial Statements included in Item 8\n of this Annual Report on Form 10-K.\n Financing\n As of December 31, 2025, we had senior unsecured notes outstanding with a total carrying value of $48.5 billion, of\n which $2.0 billion was short-term. The associated short-term and long-term future interest payments were $1.8 billion and\n $35.7 billion, respectively.\n During 2025, we issued $22.5 billion of US dollar-denominated senior unsecured notes and \u20ac13.25 billion of euro-\n denominated senior unsecured notes for general corporate purposes, comprised of the following:\n \u2022 May 2025: We issued $5.0 billion of US dollar-denominated fixed-rate senior unsecured notes with a weighted-\n average coupon rate of 4.89%, and a weighted-average maturity of approximately 24 years. We also issued \u20ac6.75\n billion of euro-denominated fixed-rate senior unsecured notes with a weighted-average coupon rate of 3.31%, and\n a weighted-average maturity of approximately 14 years.\n \u2022 November 2025: We issued $500 million of US dollar-denominated floating-rate senior unsecured notes and\n $17.0 billion of US dollar-denominated fixed-rate senior unsecured notes with a weighted-average coupon rate of\n 4.92% and a weighted-average maturity of approximately 20 years. We also issued \u20ac6.5 billion of euro-\n denominated fixed-rate senior unsecured notes with a weighted-average coupon rate of 3.44% and a weighted-\n average maturity of approximately 16 years.\n As of December 31, 2025, we had $10.0 billion of revolving credit facilities, $4.0 billion expiring in April 2026 and $6.0\n billion expiring in April 2030. No amounts have been borrowed under the credit facilities. We also have a commercial paper\n program of up to $25.0 billion, which is used for general corporate purposes. As of December 31, 2025, we had no\n commercial paper outstanding.\n For additional information, see Note 6 of the Notes to Consolidated Financial Statements included in Item 8 of this\n Annual Report on Form 10-K.\n We use contract manufacturers for our technical infrastructure and device assembly and may supply them with\n components purchased directly from suppliers. Certain of these arrangements result in a portion of the cash received from\n and paid to contract manufacturers to be presented as financing activities on the Consolidated Statements of Cash Flows\n included in Item 8 of this Annual Report on Form 10-K.\n Share Repurchase Program\n During 2025, we repurchased and subsequently retired 240 million shares for $45.4 billion.\n In April 2024, the company's Board of Directors authorized a $70.0 billion share repurchase program for its Class A\n and Class C shares. In April 2025, the company's Board of Directors authorized an additional $70.0 billion share\n repurchase program for its Class A and Class C shares. As of December 31, 2025, $69.5 billion remained available for\n Class A and Class C share repurchases.\n For additional information, see Note 11 of the Notes to Consolidated Financial Statements included in Item 8 of this\n Annual Report on Form 10-K.\n Dividend Program\n During the year ended December 31, 2025, total cash dividends were $4.8 billion for Class A, $703 million for Class\n B, and $4.5 billion for Class C shares, respectively.\n In April 2025, the company's Board of Directors increased the quarterly cash dividend by 5% to $0.21 per share of\n outstanding Class A, Class B, and Class C shares.\n The company has declared a quarterly cash dividend in the current quarter, and intends to pay quarterly cash\n dividends in the future, subject to review and approval by the company\u2019s Board of Directors in its sole discretion.\n Accrued Legal and Regulatory\n As of December 31, 2025, we had short-term accrued legal and regulatory fines and settlements of $15.6 billion. This\n amount primarily included EC fines, in addition to accruals related to other legal matters and regulatory fines and\n settlements. For additional information, see Note 10 of the Notes to Consolidated Financial Statements included in Item 8\n of this Annual Report on Form 10-K.\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 70/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 18 of 19\n Table of Contents Alphabet Inc.\n\n\n\n Alphabet Inc.\n CONSOLIDATED STATEMENTS OF CASH FLOWS\n (in millions)\n Year Ended December 31,\n 2023 2024 2025\n Operating activities\n Net income $ 73,795 $ 100,118 $ 132,170\n Adjustments:\n Depreciation of property and equipment 11,946 15,311 21,136\n Stock-based compensation expense 22,460 22,785 24,953\n Deferred income taxes (7,763) (5,257) 8,348\n Loss (gain) on debt and equity securities, net 823 (2,671) (24,620)\n Other 4,330 3,419 2,108\n Changes in assets and liabilities, net of effects of acquisitions:\n Accounts receivable, net (7,833) (5,891) (8,779)\n Income taxes, net 523 (2,418) (3,226)\n Other assets (2,143) (1,397) (4,542)\n Accounts payable 664 359 907\n Accrued expenses and other liabilities 3,937 (1,161) 12,939\n Accrued revenue share 482 1,059 899\n Deferred revenue 525 1,043 2,420\n Net cash provided by operating activities 101,746 125,299 164,713\n Investing activities\n Purchases of property and equipment (32,251) (52,535) (91,447)\n Purchases of marketable securities (77,858) (86,679) (103,773)\n Maturities and sales of marketable securities 86,672 103,428 83,240\n Purchases of non-marketable securities (3,027) (5,034) (5,716)\n Maturities and sales of non-marketable securities 947 882 1,367\n Acquisitions, net of cash acquired, and purchases of intangible assets (495) (2,931) (1,592)\n Other investing activities (1,051) (2,667) (2,370)\n Net cash used in investing activities (27,063) (45,536) (120,291)\n Financing activities\n Net payments related to stock-based award activities (9,837) (12,190) (14,167)\n Repurchases of stock (61,504) (62,222) (45,709)\n Dividend payments 0 (7,363) (10,049)\n Proceeds from issuance of debt, net of costs 10,790 13,589 64,564\n Repayments of debt (11,550) (12,701) (32,427)\n Proceeds from sale of interest in consolidated entities, net 8 1,154 400\n Net cash used in financing activities (72,093) (79,733) (37,388)\n Effect of exchange rate changes on cash and cash equivalents (421) (612) 208\n Net increase (decrease) in cash and cash equivalents 2,169 (582) 7,242\n Cash and cash equivalents at beginning of period 21,879 24,048 23,466\n Cash and cash equivalents at end of period $ 24,048 $ 23,466 $ 30,708\n Supplemental disclosures of non-cash investing activities:\n Purchases of property and equipment included in accrued liabilities and\n accounts payable $ 7,435 $ 10,326 $ 15,090\n\n See accompanying notes.\n\n\n\n 52.\n\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 87/156\n\f8/24/26, 8:46 PM Case 7:26-mc-00324-LS Document 7-3goog-20251231\n Filed 08/25/26 Page 19 of 19\n Table of Contents Alphabet Inc.\n\n\n\n\n Alphabet Inc.\n NOTES TO CONSOLIDATED FINANCIAL STATEMENTS\n Note 1. Summary of Significant Accounting Policies\n Nature of Operations\n Google was incorporated in California in September 1998 and re-incorporated in the State of Delaware in August\n 2003. In 2015, we implemented a holding company reorganization, and as a result, Alphabet Inc. (\"Alphabet\") became the\n successor issuer to Google.\n We generate revenues by delivering relevant, cost-effective online advertising; cloud-based solutions that provide\n enterprise customers of all sizes with infrastructure, platform services, and applications; and sales of other products and\n services, such as fees received for subscription-based products, apps and in-app purchases, and devices.\n Basis of Consolidation\n The consolidated financial statements of Alphabet include the accounts of Alphabet and entities consolidated under\n the variable interest and voting models. Intercompany balances and transactions have been eliminated.\n Use of Estimates\n Preparation of consolidated financial statements in conformity with GAAP requires us to make estimates and\n assumptions that affect the amounts reported and disclosed in the financial statements and the accompanying notes.\n Actual results could differ materially from these estimates due to uncertainties. On an ongoing basis, we evaluate our\n estimates, including those related to the allowance for credit losses; contingent liabilities; fair values of financial\n instruments and goodwill; income taxes; inventory; and useful lives of property and equipment, among others. We base our\n estimates on assumptions, both historical and forward looking, that are believed to be reasonable, and the results of which\n form the basis for making judgments about the carrying values of assets and liabilities.\n Revenue Recognition\n Revenues are recognized when control of the promised goods or services is transferred to our customers, and the\n collectibility of an amount that we expect in exchange for those goods or services is probable. Sales and other similar\n taxes are excluded from revenues.\n Google Advertising\n Google advertising revenues consist of revenues from:\n \u2022 Google Search and other properties, including revenues from traffic generated by search distribution partners who\n use Google.com as their default search in browsers, toolbars, etc. and other Google owned and operated\n properties like Gmail, Google Maps, and Google Play;\n \u2022 YouTube properties; and\n \u2022 Google Network properties, including revenues from Google Network properties participating in AdMob, AdSense,\n and Google Ad Manager.\n Our customers generally purchase advertising inventory through Google Ads, Google Ad Manager, Google Display &\n Video 360, and Google Marketing Platform, among others.\n We offer advertising by delivering both performance and brand advertising. We recognize revenues for performance\n advertising when a user engages with the advertisement. For brand advertising, we recognize revenues when the ad is\n displayed, or a user views the ad.\n For ads placed on Google Network properties, we evaluate whether we are the principal (i.e., report revenues on a\n gross basis) or agent (i.e., report revenues on a net basis). Generally, we report advertising revenues for ads placed on\n Google Network properties on a gross basis, that is, the amounts billed to our customers are recorded as revenues, and\n amounts paid to Google Network partners are recorded as cost of revenues. Where we are the principal, we control the\n advertising inventory before it is transferred to our customers. Our control is evidenced by our sole ability to monetize the\n advertising inventory before it is transferred to our customers and is further supported by us being primarily responsible to\n our customers and having a level of discretion in establishing pricing.\n Google Subscriptions, Platforms, and Devices\n\n\nhttps://www.sec.gov/Archives/edgar/data/1652044/000165204426000018/goog-20251231.htm 88/156\n\f","ocr_status":1,"date_upload":"2026-08-26T06:58:17.229195-07:00","document_number":"7","attachment_number":3,"pacer_doc_id":"181037269167","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit B to Jaffe Decl - 10-K 2025 Alphabet Inc.","acms_document_guid":""}],"date_created":"2026-08-25T16:17:17.556855-07:00","date_modified":"2026-08-26T06:55:12.453113-07:00","date_filed":"2026-08-25","time_filed":"18:09:37","entry_number":7,"recap_sequence_number":"2026-08-25.001","pacer_sequence_number":23,"description":"Memorandum in Opposition to Motion, filed by Google, Inc., re 1 MOTION to Compel Compliance with Subpoena Served on Third-Party Google, LLC filed by Petitioner Neural AI, LLC (Attachments: # 1 Declaration of Jordan R. Jaffe, # 2 Exhibit A to Jaffe Decl - Email Chain re Subpoena, # 3 Exhibit B to Jaffe Decl - 10-K 2025 Alphabet Inc.)(Storck, Jason) (Entered: 08/25/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/475263986/","id":475263986,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490791025/","id":490791025,"tags":[],"absolute_url":"/docket/74667129/6/neural-ai-llc-v-google-inc/","date_created":"2026-08-20T15:05:18.640249-07:00","date_modified":"2026-08-23T04:51:04.338551-07:00","sha1":"67aef55ab2324eb7052f3d557f1e4ab6494a1c91","page_count":1,"file_size":128096,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.6.0.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.6.0.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":" Case 7:26-mc-00324-LS Document 6 Filed 08/20/26 Page 1 of 1\n\n\n\n\n IN THE UNITED STATES DISTRICT COURT\n FOR THE WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\n NEURAL AI, LLC, \u00a7\n Plaintiff, \u00a7\n \u00a7\n v. \u00a7\n \u00a7 NO: MO:26-MC-00324\n GOOGLE, INC., \u00a7 (Principal Case: MO:24-CV-221-LS-DTG)\n Defendant. \u00a7\n \u00a7\n\n\n\n ORDER TO TRANSFER\n\n The above-named and numbered case is transferred from the docket of U.S. District\nJudge David Counts to the docket of U.S. District Judge Leon Schydlower both judges having\nconsented to the transfer.\n It is therefore ORDERED the above-named and numbered case is hereby\nTRANSFERRED to the docket of U.S. District Judge Leon Schydlower. Pursuant to the Order\nAssigning the Business of the Court, the Clerk shall credit this case to the percentage of business\nof the receiving Judge. All Orders shall remain in effect unless otherwise ordered by Judge Leon\nSchydlower.\n It is so ORDERED.\n SIGNED this 20th day of August, 2026.\n\n\n\n\n DAVID COUNTS\n UNITED STATES DISTRICT JUDGE\n\f","ocr_status":2,"date_upload":"2026-08-20T20:07:17.790653-07:00","document_number":"6","attachment_number":null,"pacer_doc_id":"181037241846","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Order Reassigning Case","acms_document_guid":""}],"date_created":"2026-08-20T15:05:18.615909-07:00","date_modified":"2026-08-20T20:06:48.200511-07:00","date_filed":"2026-08-20","time_filed":"16:20:48","entry_number":6,"recap_sequence_number":"2026-08-20.001","pacer_sequence_number":20,"description":"ORDER REASSIGNING CASE. Case reassigned to District Judge Leon Schydlower for all proceedings. Judge David Counts no longer assigned to case. Signed by Judge David Counts. (llm) (Entered: 08/20/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/475029067/","id":475029067,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490548017/","id":490548017,"tags":[],"absolute_url":"/docket/74667129/5/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T08:36:42.818511-07:00","date_modified":"2026-08-23T02:44:36.644751-07:00","sha1":"96207c6fa61684a11c9102c6bda87dd0ea763283","page_count":1,"file_size":190432,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.5.0.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.5.0.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":" Case 7:26-mc-00324-DC Document 5 Filed 08/19/26 Page 1 of 1\n\n\n\n\n UNITED STATES DISTRICT COURT\nPHILIP J. DEVLIN WESTERN DISTRICT OF TEXAS ANNETTE FRENCH\n CLERK OF COURT 200 E. Wall Street, Suite 222 CHIEF DEPUTY\n Midland, TX 79701\n August 19, 2026\n\n Emily Portuguese\n One Manhattan West, 50th Floor\n New Your, NY 10001\n\n Re: 7:26-MC-00324 Neural AI, LLC v. Google, Inc.\n\n Dear Counsel:\n\n Our records indicate that you are not admitted to practice in the Western District of Texas. Local\n Court Rule AT-1(f)(1) states:\n\n In General: An attorney who is licensed by the highest court of a state or another\n federal district court, but who is not admitted to practice before this court, may\n represent a party in this court pro hac vice only by permission of the judge\n presiding. Unless excused by the judge presiding, an attorney is ordinarily required\n to apply for admission to the bar of this court.\n\n Pursuant to Local Court Rule AT-2, if you are an attorney residing outside the Western District\n of Texas, the court may require you to designate local counsel in this case.\n\n Please submit a Motion to Appear Pro Hac Vice requesting the Court\u2019s permission to appear in\n the above-captioned cause, along with a $100 filing fee. Applications for permanent admission\n to the bar and Local Court Rules for the Western District of Texas are available on our website at\n www.txwd.uscourts.gov.\n\n Please be advised that the Clerk no longer automatically adds non-admitted attorneys to a\n case. Thus, non-admitted attorneys will not receive orders or notices (which may include\n deadlines, hearing dates, etc.) filed in their case. The Clerk will only add said attorneys to\n the case upon the granting of a Motion to Appear pro hac vice.\n\n Sincerely,\n\n KM\n Deputy Clerk\n\n KM\n\f","ocr_status":2,"date_upload":"2026-08-20T10:55:11.307922-07:00","document_number":"5","attachment_number":null,"pacer_doc_id":"181037222072","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Pro Hac Vice Letter","acms_document_guid":""}],"date_created":"2026-08-19T08:36:42.763667-07:00","date_modified":"2026-08-19T14:33:03.374146-07:00","date_filed":"2026-08-19","time_filed":"10:14:22","entry_number":5,"recap_sequence_number":"2026-08-19.003","pacer_sequence_number":18,"description":"Pro Hac Vice Letter for Attorney Emily Portuguese. (ktm) (Entered: 08/19/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/475024299/","id":475024299,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490543207/","id":490543207,"tags":[],"absolute_url":"","date_created":"2026-08-19T08:19:20.031425-07:00","date_modified":"2026-08-19T08:19:20.031438-07:00","sha1":"","page_count":null,"file_size":null,"filepath_local":null,"filepath_ia":"","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"","ocr_status":null,"date_upload":null,"document_number":"","attachment_number":null,"pacer_doc_id":"","is_available":false,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Case Assigned/Reassigned","acms_document_guid":""}],"date_created":"2026-08-19T08:19:20.020196-07:00","date_modified":"2026-08-19T08:19:20.020209-07:00","date_filed":"2026-08-19","time_filed":"10:07:55","entry_number":null,"recap_sequence_number":"2026-08-19.001","pacer_sequence_number":null,"description":"","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/475024283/","id":475024283,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490543191/","id":490543191,"tags":[],"absolute_url":"/docket/74667129/3/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T08:19:18.504000-07:00","date_modified":"2026-08-22T23:48:44.954382-07:00","sha1":"ee50dfc01f5289228e9a8c7e1df78a7adaea8b68","page_count":1,"file_size":191695,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.3.0.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.3.0.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":" Case 7:26-mc-00324-DC Document 3 Filed 08/19/26 Page 1 of 1\n\n\n\n\n UNITED STATES DISTRICT COURT\nPHILIP J. DEVLIN WESTERN DISTRICT OF TEXAS ANNETTE FRENCH\n CLERK OF COURT 200 E. Wall Street, Suite 222 CHIEF DEPUTY\n Midland, TX 79701\n August 19, 2026\n\n Samuel Drezdzon\n SUSMAN GODFREY L.L.P.\n 1000 Louisiana, Suite 5100\n Houston, TX 77002\n\n Re: 7:26-MC-00324 Neural AI, LLC v. Google, Inc.\n\n Dear Counsel:\n\n Our records indicate that you are not admitted to practice in the Western District of Texas. Local\n Court Rule AT-1(f)(1) states:\n\n In General: An attorney who is licensed by the highest court of a state or another\n federal district court, but who is not admitted to practice before this court, may\n represent a party in this court pro hac vice only by permission of the judge\n presiding. Unless excused by the judge presiding, an attorney is ordinarily required\n to apply for admission to the bar of this court.\n\n Pursuant to Local Court Rule AT-2, if you are an attorney residing outside the Western District\n of Texas, the court may require you to designate local counsel in this case.\n\n Please submit a Motion to Appear Pro Hac Vice requesting the Court\u2019s permission to appear in\n the above-captioned cause, along with a $100 filing fee. Applications for permanent admission\n to the bar and Local Court Rules for the Western District of Texas are available on our website at\n www.txwd.uscourts.gov.\n\n Please be advised that the Clerk no longer automatically adds non-admitted attorneys to a\n case. Thus, non-admitted attorneys will not receive orders or notices (which may include\n deadlines, hearing dates, etc.) filed in their case. The Clerk will only add said attorneys to\n the case upon the granting of a Motion to Appear pro hac vice.\n\n Sincerely,\n\n KM\n Deputy Clerk\n\n KM\n\f","ocr_status":2,"date_upload":"2026-08-20T10:55:13.765602-07:00","document_number":"3","attachment_number":null,"pacer_doc_id":"181037222000","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Pro Hac Vice Letter","acms_document_guid":""}],"date_created":"2026-08-19T08:19:18.477217-07:00","date_modified":"2026-08-19T08:36:42.695273-07:00","date_filed":"2026-08-19","time_filed":"10:10:23","entry_number":3,"recap_sequence_number":"2026-08-19.001","pacer_sequence_number":14,"description":"Pro Hac Vice Letter for Attorney Samuel Drezdzon. (ktm) (Entered: 08/19/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/475024251/","id":475024251,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490543159/","id":490543159,"tags":[],"absolute_url":"/docket/74667129/4/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T08:19:15.239856-07:00","date_modified":"2026-08-23T06:02:47.231384-07:00","sha1":"4bab173ea4b6a5bae1591f366a09e99dbcd6edba","page_count":1,"file_size":190234,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.4.0.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.4.0.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":" Case 7:26-mc-00324-DC Document 4 Filed 08/19/26 Page 1 of 1\n\n\n\n\n UNITED STATES DISTRICT COURT\nPHILIP J. DEVLIN WESTERN DISTRICT OF TEXAS ANNETTE FRENCH\n CLERK OF COURT 200 E. Wall Street, Suite 222 CHIEF DEPUTY\n Midland, TX 79701\n August 19, 2026\n\n Tamar Lusztig\n One Manhattan West, 50th Floor\n New Your, NY 10001\n\n Re: 7:26-MC-00324 Neural AI, LLC v. Google, Inc.\n\n Dear Counsel:\n\n Our records indicate that you are not admitted to practice in the Western District of Texas. Local\n Court Rule AT-1(f)(1) states:\n\n In General: An attorney who is licensed by the highest court of a state or another\n federal district court, but who is not admitted to practice before this court, may\n represent a party in this court pro hac vice only by permission of the judge\n presiding. Unless excused by the judge presiding, an attorney is ordinarily required\n to apply for admission to the bar of this court.\n\n Pursuant to Local Court Rule AT-2, if you are an attorney residing outside the Western District\n of Texas, the court may require you to designate local counsel in this case.\n\n Please submit a Motion to Appear Pro Hac Vice requesting the Court\u2019s permission to appear in\n the above-captioned cause, along with a $100 filing fee. Applications for permanent admission\n to the bar and Local Court Rules for the Western District of Texas are available on our website at\n www.txwd.uscourts.gov.\n\n Please be advised that the Clerk no longer automatically adds non-admitted attorneys to a\n case. Thus, non-admitted attorneys will not receive orders or notices (which may include\n deadlines, hearing dates, etc.) filed in their case. The Clerk will only add said attorneys to\n the case upon the granting of a Motion to Appear pro hac vice.\n\n Sincerely,\n\n KM\n Deputy Clerk\n\n KM\n\f","ocr_status":2,"date_upload":"2026-08-20T10:55:11.489709-07:00","document_number":"4","attachment_number":null,"pacer_doc_id":"181037222049","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Pro Hac Vice Letter","acms_document_guid":""}],"date_created":"2026-08-19T08:19:15.214680-07:00","date_modified":"2026-08-19T08:36:42.730050-07:00","date_filed":"2026-08-19","time_filed":"10:13:14","entry_number":4,"recap_sequence_number":"2026-08-19.002","pacer_sequence_number":16,"description":"Pro Hac Vice Letter for Attorney Tamar Lusztig. (ktm) (Entered: 08/19/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/474996184/","id":474996184,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514513/","id":490514513,"tags":[],"absolute_url":"/docket/74667129/2/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:48:57.461500-07:00","date_modified":"2026-08-19T03:48:57.461522-07:00","sha1":"","page_count":null,"file_size":null,"filepath_local":null,"filepath_ia":"","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"","ocr_status":null,"date_upload":null,"document_number":"2","attachment_number":null,"pacer_doc_id":"","is_available":false,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"","acms_document_guid":""}],"date_created":"2026-08-19T03:48:57.430662-07:00","date_modified":"2026-08-19T03:48:57.441335-07:00","date_filed":"2026-08-18","time_filed":null,"entry_number":2,"recap_sequence_number":"2026-08-18.002","pacer_sequence_number":null,"description":"Miscellaneous Filing fee received in the amount of $52, receipt number ATXWDC-22497838. (Magni, Rocco) (Entered: 08/18/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/474970643/","id":474970643,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490487440/","id":490487440,"tags":[],"absolute_url":"/docket/74667129/1/neural-ai-llc-v-google-inc/","date_created":"2026-08-18T17:13:30.508064-07:00","date_modified":"2026-08-22T23:36:08.795770-07:00","sha1":"3ad12e5dbf1eec6723f3dc63def2cd6bc80dd776","page_count":16,"file_size":342966,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.0.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.0.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":" Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 1 of 16\n\n\n\n\n IN THE UNITED STATES DISTRICT COURT\n FOR THE WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\n\nNEURAL AI, LLC,\n Misc. Case No. 7:26-mc-324\n Petitioner,\n Principal case pending in Western District of\n v. Texas, Civil Action No. 7:24-cv-00221-LS-\n DTG\nGOOGLE, LLC,\n\n Respondent.\n\n\n NEURAL AI\u2019S MOTION TO COMPEL COMPLIANCE WITH\n SUBPOENA SERVED ON THIRD-PARTY GOOGLE, LLC\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 2 of 16\n\n\n\n\n TABLE OF CONTENTS\n\nI. FACTUAL BACKGROUND ............................................................................................. 1\n\n A. The Underlying Litigation ...................................................................................... 2\n\n B. The Rule 45 Subpoena to Google and Google\u2019s Initial Objections ........................ 3\n\n C. NAI\u2019s Meet-and-Confer Efforts and Google\u2019s Continued Non-Compliance ......... 3\n\nII. THE COURT HAS JURISDICTION BECAUSE THE PLACE OF COMPLIANCE IN\n AUSTIN IS PROPER. ........................................................................................................ 5\n\nIII. GOOGLE MUST PRODUCE DOCUMENTS RESPONSIVE TO THE SUBPOENA. ... 6\n\n A. The Requested Discovery Goes to the Heart of NAI\u2019s Infringement Claims......... 7\n\n B. Google Has Not Substantiated Burden and NAI Offered Narrower Alternatives. . 9\n\nIV. CONCLUSION ................................................................................................................. 10\n\n\n\n\n i\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 3 of 16\n\n\n\n\n TABLE OF AUTHORITIES\n\n Page(s)\n\nCases\n\n611 Carpenter LLC v. Atlantic Casualty Ins. Co.,\n 2024 WL 1977160 (W.D. Tex. Apr. 30, 2024)................................................................6, 9, 10\n\nCamoco, LLC v. Leyva,\n 333 F.R.D. 603 (W.D. Tex. 2019) .............................................................................................6\n\nConservation L. Found., Inc. v. Equilon Enters. LLC,\n 2025 WL 2821238 (D.R.I. Oct. 3, 2025) ...................................................................................5\n\nFG SRC LLC v. Xilinx, Inc.,\n 2022 WL 22997130 (D. Del. Apr. 11, 2022) .............................................................................8\n\nFlores v. Lowes Home Centers, L.L.C,\n 2023 WL 3959399 (W.D. Tex. June 12, 2023) .........................................................................6\n\nKim v. NuVasive, Inc.,\n 2011 WL 3844106 (S.D. Cal. Aug. 29, 2011) ...........................................................................8\n\nLucent Technologies, Inc. v. Gateway, Inc.,\n 580 F.3d 1301 (Fed. Cir. 2009)..................................................................................................8\n\nMeritage Homes, LLC v. AIG Specialty Ins. Co.,\n 2024 WL 221448 (W.D. Tex. Jan. 18, 2024) ............................................................................5\n\nNeural AI, LLC v. NVIDIA Corp.,\n Case No. 7:24-cv-00221-LS-DTG (W.D. Tex.) ................................................................1, 2, 5\n\nTrs. of Bos. Univ. v. Everlight Elecs. Co.,\n 2014 WL 12792496 (D. Mass. Sept. 8, 2014) ...........................................................................5\n\nVelocity Pat. LLC v. FCA US LLC,\n 2017 WL 11893112 (N.D. Ill. Nov. 2, 2017) ............................................................................6\n\nWaller v. Jet Specialty, Inc.,\n 2024 WL 7050192 (W.D. Tex. Nov. 19, 2024) .........................................................................6\n\nRules\n\nFed. R. Civ. P. 26 .............................................................................................................................6\n\nFed. R. Civ. P. 26(b)(1)....................................................................................................................6\n\nFed. R. Civ. P. 45 .................................................................................................................1, 3, 5, 6\n\n\n ii\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 4 of 16\n\n\n\n\nFed. R. Civ. P. 45(c) ........................................................................................................................5\n\nFed. R. Civ. P. 45(c)(2)(A) ..............................................................................................................5\n\nFed. R. Civ. P. 45(d)(2)(B)(i) ......................................................................................................5, 6\n\n\n\n\n iii\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 5 of 16\n\n\n\n\n This motion arises from Neural AI, LLC v. NVIDIA Corp., Case No. 7:24-cv-00221-LS-\n\nDTG (W.D. Tex.) (the \u201cUnderlying Action\u201d), a patent-infringement action pending in this District.\n\nIn the Underlying Action, Neural AI, LLC (\u201cNAI\u201d) alleges that Defendant NVIDIA Corporation\n\n(\u201cNVIDIA\u201d) infringes through its GPU-accelerated hardware and software: U.S. Patent No.\n\n8,648,867 (the \u201c\u2019867 Patent\u201d), Reissue Patent No. RE48,438 (the \u201c\u2019438 Patent\u201d), and Reissue\n\nPatent No. RE49,461 (the \u201c\u2019461 Patent\u201d) (collectively, the \u201cAsserted Patents\u201d). See Exhibits 1\u20134.\n\n NVIDIA has made customer deployment central to the Underlying Action. It disputes\n\nwhether customers configure and use the accused products as NAI alleges and contends that NAI\n\nmust obtain customer evidence to prove indirect infringement. See Laiche Decl. \u00b6\u00b6 24\u201325.\n\nRespondent Google, LLC (\u201cGoogle\u201d) is one of NVIDIA\u2019s largest customers and end users. Its\n\nrecords and testimony therefore contain the real-world evidence NVIDIA says NAI must obtain.\n\n NAI served Google on June 25, 2026, with Rule 45 subpoenas seeking targeted documents\n\nand corporate testimony concerning Google\u2019s configuration, integration, and use of NVIDIA\n\nGPUs and software. Google objected to every document request and deposition topic and has\n\nproduced no documents and designated no witness. The parties have since met and conferred on\n\nthree separate occasions, and NAI has repeatedly offered less burdensome alternatives to resolve\n\nthe dispute. Among other things, NAI provided focused technical questions and proposed a draft\n\ndeclaration that Google could execute in lieu of document production and deposition testimony.\n\n Those efforts have not resolved the dispute. Despite three conferences and numerous\n\nfollow-up emails, Google has not committed to producing responsive documents, designating a\n\nwitness, or providing an executed declaration addressing the relevant facts. See Exhibits 11\u201314,\n\n20; Laiche Decl. \u00b6 26. NAI therefore asks the Court to compel Google to produce documents\n\nresponsive to Requests 1\u201312 on a rolling basis by dates certain and to designate and produce a\n\n\n\n\n 1\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 6 of 16\n\n\n\n\nknowledgeable corporate representative to testify on Deposition Topics 1\u20135.\n\nI. FACTUAL BACKGROUND\n\n A. The Underlying Litigation\n\n The Underlying Action involves direct, indirect, and induced infringement claims\n\nconcerning claims 16\u201319 of the \u2019867 Patent; claims 1, 3\u20136, 8\u20139, 12, 14, 17\u201318, 21\u201323, 29\u201330, 32,\n\n40, 43\u201344, 46, 48, 51\u201352, and 55\u201357 of the \u2019438 Patent; and claims 21\u201325 and 27\u201330 of the \u2019461\n\nPatent (collectively, the \u201cAsserted Claims\u201d). See Exhibits 1 and 7. The Asserted Patents teach\n\nGPU-accelerated computing systems and methods. See Exhibits 2\u20134.\n\n NAI\u2019s January 20, 2026 Final Infringement Contentions identify integrated combinations of\n\nNVIDIA hardware\u2014including GPUs, supercomputers and servers\u2014and GPU-accelerated software,\n\nincluding CUDA, cuDNN, TensorRT, and higher-level frameworks, as the Accused Products. See\n\nExhibit 7 at 2\u20139. NAI alleges NVIDIA encourages customers to combine, configure, and use those\n\nproducts in an infringing manner. See id. at 12\u201313.\n\n NVIDIA disputes that selling the Accused Products proves customers configure and deploy\n\nthem as NAI alleges. Although NVIDIA admits selling the Accused Products and partnering with\n\nresellers and service providers, it denies infringement and disclaims knowledge of customer use.\n\nSee Exhibit 8 \u00b6\u00b6 18, 20\u201323, 87, 131, 171. Customer evidence is therefore directly relevant to NAI\u2019s\n\ninfringement claims.\n\n Google is one of NVIDIA\u2019s largest and most significant customers, partners, and end users\n\nof the Accused Products. NVIDIA and Google Cloud have \u201ccollaborated for more than a decade,\n\nco\u2011engineering a full\u2011stack AI platform that spans every technology layer\u2014from\n\nperformance\u2011optimized libraries and frameworks to enterprise\u2011grade cloud services.\u201d See Exhibit\n\n15 at 1. Google Cloud offers its customers NVIDIA GPU instances. See Exhibits 15\u201316. Google\n\n\n\n\n 2\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 7 of 16\n\n\n\n\nis thus a real-world integrator, user, and deployer of the accused GPU-acceleration hardware and\n\nsoftware. Its documents concerning the configuration, integration, deployment, and use of those\n\nproducts bear directly on whether the Accused Products are used in an infringing manner and\n\nwhether NVIDIA induced or contributed to that infringement.\n\n B. The Rule 45 Subpoena to Google and Google\u2019s Initial Objections\n\n NAI served Google on June 25, 2026, with Rule 45 subpoenas for documents and corporate\n\ntestimony, designating Austin, Texas, as the place of compliance. See Exhibits 5\u20136. The document\n\nsubpoena contains twelve targeted requests directed to how Google configures, integrates, and uses\n\nNVIDIA GPUs and related software. See Exhibit 5. The accompanying deposition subpoena seeks\n\ntestimony on the same core subjects across five topics. See id. Both subpoenas are limited to\n\nSeptember 13, 2018 to the present and to U.S.-based or U.S.-directed activity. See, e.g., id. at 12.\n\n Google\u2019s responses were due July 14, 2026. At Google\u2019s request, NAI extended the\n\ndeadline to July 21. See Exhibit 11 at 1. Google then objected to every request and topic on\n\nboilerplate grounds, refused to produce any documents or designate a witness. See Exhibits 9\u201310.\n\nNAI thus has received no discovery concerning Google\u2019s real-world configuration and use of the\n\naccused NVIDIA products, which is the evidence NVIDIA says NAI must obtain to prove indirect\n\ninfringement and damages.\n\n C. NAI\u2019s Meet-and-Confer Efforts and Google\u2019s Continued Non-Compliance\n\n The parties first met and conferred on or around July 25, 2026. See Exhibit 12 at 2. NAI\n\nexplained that the Subpoenas seek targeted discovery into how Google configures and uses\n\nNVIDIA GPUs and related software. Google said it was still investigating and needed to consult\n\ntechnical personnel. On July 28, NAI provided Google with a draft declaration, invited Google to\n\nrevise it, and offered to consider an executed declaration in lieu of broader document production\n\n\n\n\n 3\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 8 of 16\n\n\n\n\nand deposition testimony, subject to resolving material gaps. See Exhibit 13. The parties met again\n\non August 1, 2026, and Google said it was continuing its investigation. Id.\n\n On August 4, 2026, NAI supplied focused technical questions and recirculated the draft\n\ndeclaration, again confirming that \u201cIf Google commits to provide an executed declaration, Neural\n\nAI is willing to consider accepting the declaration in lieu of further document production and/or\n\ndeposition testimony, subject to resolving any material gaps.\u201d See Exhibit 12 at 1; Exhibits 13\u201314.\n\nOn August 6, 2026, Google responded that NAI\u2019s requests, questions, and draft declaration were\n\n\u201coverbroad and unduly burdensome for a third party.\u201d Exhibit 20 at 8. It said it was \u201cinvestigating\n\nthe topics covered in the \u2018template\u2019 declaration\u201d and \u201cmay be able to provide a declaration within\n\na more reasonable scope,\u201d but demanded advance agreement that any declaration \u201csatisf[y] all of\n\nGoogle\u2019s obligations under the subpoenas.\u201d Id. NAI responded that it would accept an\n\nappropriately complete declaration but could not agree in advance that any declaration would\n\nsatisfy all obligations without confirming its contents. Id. at 7.\n\n On August 11, 2026, NAI informed Google that NVIDIA had extended the deadline for\n\nthird-party discovery motions through August 18, 2026 and asked Google to send proposed\n\ndeclaration edits promptly. Id. at 4. On Thursday, August 13 at 5:39 pm CT, Google said it had\n\n\u201can update\u201d and requested another meet-and-confer. Id. The parties spoke for the third time the\n\nfollowing Monday August 17, 2026. Id. at 1. Google\u2019s counsel raised factual issues with the\n\ndeclaration on that call, and the following day NAI sent a revised declaration addressing Google\u2019s\n\nstated concerns and offered two options to reduce the burden on Google: (1) execute a revised\n\ndeclaration addressing the identified issues without material gaps or (2) produce documents\n\nsufficient to establish those issues. See id.; Exhibit 21; Laiche Decl. \u00b6\u00b6 21\u201322.\n\n Google\u2019s counsel responded only by asserting defensively that NAI had refused to narrow\n\n\n\n\n 4\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 9 of 16\n\n\n\n\nits requests and had failed to satisfy its meet-and-confer obligations. That assertion is baseless.\n\nOver the past six weeks, NAI has participated in three separate calls, exchanged numerous emails,\n\nproposed two declarations confined to narrow issues as alternatives to broader discovery, and even\n\noffered to accept documents merely sufficient to address each issue identified in the narrowed\n\ndeclaration. Despite those repeated efforts to reduce Google\u2019s burden and resolve the dispute\n\nwithout motion practice, Google has remained noncompliant. As of filing, Google had identified\n\nno requests it would answer, produced no responsive documents, answered no technical questions,\n\nproposed no declaration revisions, made no commitment to execute a declaration, designated no\n\nwitness, and set no compliance date. See Exhibits 12, 20; Laiche Decl. \u00b6 26.\n\n Document discovery in the Underlying Action closed August 11, 2026, deposition\n\ndiscovery closes September 16, 2026, and NVIDIA agreed to extend NAI\u2019s deadline to file third-\n\nparty discovery motions related to documents through August 18, 2026. See Neural AI, LLC v.\n\nNVIDIA Corp., Case No. 7:24-cv-00221-LS-DTG, Dkt. 181 (W.D. Tex.); Laiche Decl. \u00b6 27. NAI\n\ncannot allow an open-ended investigation to consume the remaining discovery period and seeks\n\ncourt intervention while remaining willing to consider prompt and complete discovery that\n\nresolves the dispute. See Exhibit 11.\n\nII. THE COURT HAS JURISDICTION BECAUSE THE PLACE OF COMPLIANCE\n IN AUSTIN IS PROPER.\n\n Rule 45(d)(2)(B)(i) directs a party seeking to compel compliance to apply to \u201cthe court for\n\nthe district where compliance is required.\u201d Fed. R. Civ. P. 45(d)(2)(B)(i); see also Meritage\n\nHomes, LLC v. AIG Specialty Ins. Co., 2024 WL 221448, at *4 (W.D. Tex. Jan. 18, 2024). Rule\n\n45(c)(2)(A) permits document production \u201cat a place within 100 miles of where the person resides,\n\nis employed, or regularly transacts business in person,\u201d and the issuing party need not choose a\n\nplace within 100 miles of the recipient\u2019s headquarters. See, e.g., Conservation L. Found., Inc. v.\n\n\n\n 5\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 10 of 16\n\n\n\n\nEquilon Enters. LLC, 2025 WL 2821238, at *1 (D.R.I. Oct. 3, 2025).\n\n Austin satisfies Rule 45(c)(2)(A). Google has maintained an Austin presence for over a\n\ndecade, currently employs more than 1,100 people, has leased multiple office spaces, and invested\n\n$600 million in a Texas data center as part of a $13 billion investment. See Exhibit 18. Google\u2019s\n\nregistered agent is in Austin, and Google currently advertises 167 in-person jobs in Austin. See\n\nExhibit 6; see also Exhibits 17, 19. Google cannot credibly maintain that Austin is not a place\n\nwhere it regularly transacts business in person.\n\n Google instead objects that its likely custodians are near Mountain View, California. See\n\nExhibits 9\u201310. But Rule 45(c)(2)(A) turns on where Google regularly transacts business in person,\n\nnot where custodians or documents are located. Fed. R. Civ. P. 45; Trs. of Bos. Univ. v. Everlight\n\nElecs. Co., 2014 WL 12792496, at *3 (D. Mass. Sept. 8, 2014) (\u201cRule 45(c) says nothing about\n\nthe location of documents subpoenaed.\u201d); Velocity Pat. LLC v. FCA US LLC, 2017 WL 11893112,\n\nat *4 (N.D. Ill. Nov. 2, 2017) (rejecting argument that, \u201cregardless of its other locations,\u201d its\n\nheadquarters was the \u201conly location where it stores\u201d requested documents). Because the designated\n\nplace of compliance is proper, this Court has jurisdiction to resolve this Motion.\n\nIII. GOOGLE MUST PRODUCE DOCUMENTS RESPONSIVE TO THE SUBPOENA.\n\n Federal Rule of Civil Procedure 26 provides that a party may obtain discovery regarding\n\nany nonprivileged matter that is relevant to the parties\u2019 claims or defenses and proportional to the\n\nneeds of the case. Fed. R. Civ. P. 26(b)(1). \u201cAt the discovery stage, relevancy is broadly\n\nconstrued.\u201d Flores v. Lowes Home Centers, L.L.C., 2023 WL 3959399, at *2 (W.D. Tex. June 12,\n\n2023). \u201c\u2018[A] request for discovery should be considered relevant if there is any possibility that the\n\ninformation sought may be relevant to the claim or defense of any party.\u2019\u201d Id. (quoting Camoco,\n\nLLC v. Leyva, 333 F.R.D. 603, 606 (W.D. Tex. 2019)).\n\n\n\n\n 6\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 11 of 16\n\n\n\n\n Where, as here, a non-party refuses discovery in response to a validly issued subpoena,\n\nFederal Rule of Civil Procedure 45 provides the Court for the district where compliance is required\n\nwith broad discretion to compel the production of documents and information from third parties.\n\nFed. R. Civ. P. 45(d)(2)(B)(i). Once a party moving to compel discovery establishes that the\n\nmaterials are relevant, \u201c[t]he party opposing discovery bears the burden of stating \u2018with specificity\n\nthe grounds for objecting to the request.\u2019\u201d Waller v. Jet Specialty, Inc., 2024 WL 7050192, at *1\n\n(W.D. Tex. Nov. 19, 2024); see also 611 Carpenter LLC v. Atlantic Casualty Ins. Co., 2024 WL\n\n1977160, at *1 (W.D. Tex. Apr. 30, 2024). The non-party \u201cmust state with specificity the objection\n\nand how it relates to the particular request being opposed, and not merely that it is overly broad\n\nand burdensome.\u201d 611 Carpenter, 2024 WL 1977160, at *1.\n\n A. The Requested Discovery Goes to the Heart of NAI\u2019s Infringement Claims.\n\n NVIDIA has made customer deployment a disputed issue. It contends that selling or\n\nproviding the Accused Products does not prove customers configure and use them as alleged and\n\nthat NAI needs customer evidence to prove infringement and its extent. See Laiche Decl. \u00b6\u00b6 24\u201325.\n\nGoogle is a major customer and end user. NVIDIA and Google have \u201ccollaborated for more than a\n\ndecade, co\u2011engineering a full\u2011stack AI platform that spans every technology layer,\u201d (Exhibit 15 at 1)\n\nand Google offers NVIDIA GPU instances, including configurations powered by the accused\n\nNVIDIA Blackwell GPUs (Exhibits 15\u201316).\n\n The information is also uniquely within Google\u2019s possession. NVIDIA may know what it\n\ndesigned and distributed, but, according to NVIDIA, only Google knows what it selected,\n\nconfigured, deployed, and actually ran. NVIDIA claims it does not possess Google\u2019s internal\n\narchitecture and deployment records and has repeatedly disclaimed insight into customer\n\ndeployments. See Laiche Decl. \u00b6 25.\n\n\n\n\n 7\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 12 of 16\n\n\n\n\n The twelve document requests seek discovery tied to the Asserted Claims in the\n\nUnderlying Action, and track the accused computation from software selection through input,\n\nexecution, memory, and output to establish infringement. See Exhibit 5.\n\n \u2022 Requests 1\u20134 seek documents sufficient to identify the software, frameworks, libraries,\n configurations, and custom code Google uses on NVIDIA GPUs; the NVIDIA software\n and sample code it uses; and how Google calls, interfaces with, modifies, or extends that\n functionality. They show which accused products Google deployed and whether Google\n used them as provided and intended or materially modified them.\n\n \u2022 Requests 5\u20136 seek architecture, design, data-flow, control-flow, and execution-flow\n materials and documents showing whether the relevant computations involve neural\n networks, layers, and outputs used as inputs to later neurons or layers. They show whether\n Google\u2019s systems perform the claimed GPU-accelerated operations and how the accused\n hardware and software work together as relevant to the Asserted Claims.\n\n \u2022 Requests 7\u201310 address the claimed memory and data paths: pointer, buffer, and\n intermediate-result reuse; GPU-memory allocation or partitioning; movement of inputs\n from CPU, host, storage, or network sources into GPU memory; and storage, transfer,\n accumulation, reuse, or return of outputs and intermediate results. They target the memory-\n management and data-transfer limitations at the heart of the Asserted Claims.\n\n \u2022 Requests 11\u201312 seek documents sufficient to show how GPU computations are scheduled,\n ordered, queued, synchronized, parallelized, launched, and executed, and how inputs,\n commands, model or parameter changes, interruptions, or output changes affect GPU-\n queue placement. They target the claimed coordination and control of GPU computations.\n\nThese requests target whether Google\u2019s systems perform the asserted method steps and whether\n\nNVIDIA\u2019s software, instructions, and support cause or encourage that use. See Lucent\n\nTechnologies, Inc. v. Gateway, Inc., 580 F.3d 1301, 1321\u201322, 1333-34 (Fed. Cir. 2009) (a patentee\n\nmust show all steps of a claimed method were performed to prove indirect infringement and\n\ndamages \u201cought to be correlated, in some respect, to the extent the infringing method is used by\u201d\n\ndirectly infringing third parties); FG SRC LLC v. Xilinx, Inc., 2022 WL 22997130, at *5 (D. Del.\n\nApr. 11, 2022) (\u201c[I]t is clear that SRC has a need for information from third parties demonstrating\n\nthat the parties practice the asserted claims.\u201d); Kim v. NuVasive, Inc., 2011 WL 3844106, at *3\n\n\n\n\n 8\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 13 of 16\n\n\n\n\n(S.D. Cal. Aug. 29, 2011) (\u201cThe Court finds the information sought in the subpoenas is relevant to\n\nNuVasive's claim of induced infringement and damages therefrom\u201d).\n\n The requests are also bounded and particular. Each seeks only documents \u201csufficient to\n\nshow\u201d an identified technical fact. The Subpoena is limited to September 13, 2018 to the present\n\nand to U.S.-based or U.S.-directed activity. It does not seek every document mentioning NVIDIA,\n\na wholesale source-code production, or information about products Google does not use.\n\n The five deposition topics seek testimony on the same subjects as the document requests\n\nand directs Google to designate one or more knowledgeable persons on five topics. See Exhibit 5.\n\n \u2022 Topic 1: the NVIDIA software and libraries Google uses to perform computations on\n NVIDIA GPUs;\n\n \u2022 Topic 2: NVIDIA sample source code Google uses, in whole or in part;\n\n \u2022 Topic 3: Google\u2019s customizations and data inputs that alter how NVIDIA software\n performs computations;\n\n \u2022 Topic 4: identification of Google software that uses NVIDIA GPUs to perform\n computations; and\n\n \u2022 Topic 5: how output and intermediate GPU results are stored, referenced by pointers,\n transferred, copied, streamed, written back, returned, accumulated, reused, or otherwise\n made available between GPU memory and CPU, host, system, storage, display,\n network, or other memory locations.\n\nThe testimony is proportional because it is limited to five topics tracking the twelve requests, the\n\nsame defined period, and the same U.S. nexus, and NVIDIA claims it cannot supply Google\u2019s\n\ninternal configuration or operating practices.\n\n The information is central to the issues in dispute, uniquely within Google\u2019s possession, and\n\nsought through targeted requests and topics. Google should be compelled to produce it.\n\n B. Google Has Not Substantiated Burden and NAI Offered Narrower\n Alternatives.\n\n Google\u2019s written objections do not \u201cstate with specificity\u201d the burden Google would face\n\n\n\n 9\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 14 of 16\n\n\n\n\nin producing responsive documents. 611 Carpenter LLC, 2024 WL 1977160, at *1. Google\n\nrepeated the same boilerplate objections across all twelve requests and five topics and then refused\n\nto produce documents or designate a witness. See Exhibits 9\u201310. Boilerplate objections\n\nunsupported by evidence of burden are not sufficient.\n\n Google\u2019s objection that \u201cNVIDIA GPUs\u201d is vague and overbroad because the definition\n\nspans multiple pages and covers \u201chundreds of GPU architectures\u201d does not show burden. See\n\nExhibit 9 at 6. The definition tracks the Accused Products identified in NAI\u2019s infringement\n\ncontentions (Exhibit 7 at 2\u20139), and the requests seek documents \u201csufficient to show\u201d facts about\n\nproducts Google actually deploys. See Exhibits 5, 7, 9.\n\n NAI minimized burden at every turn. Before subpoenaing Google, NAI first sought the\n\ninformation from NVIDIA. After service, NAI extended Google\u2019s response deadline, identified\n\nthe implicated products and systems, supplied focused technical questions, offered a draft\n\ndeclaration in lieu of broader document discovery and testimony, and invited Google to identify\n\nany specific burdens. See Exhibits 11\u201314. NAI then offered two concrete paths to resolution:\n\nGoogle could either (1) execute a revised declaration addressing the identified issues without\n\nmaterial gaps or (2) produce documents sufficient to establish those same facts. See Exhibit 20;\n\nLaiche Decl. \u00b6\u00b6 21\u201322. Google chose neither. See Exhibit 20; Laiche Decl. \u00b6 26. Google cannot\n\nplausibly argue NAI refused to narrow and invoke burden as a basis for producing nothing.\n\nIV. CONCLUSION\n\n NAI respectfully requests that this Court enter an order (1) compelling Google to produce\n\nnonprivileged documents responsive to Requests 1\u201312 on a rolling basis to be completed within\n\ntwenty-one (21) days of the Court\u2019s order, and (2) compelling Google to designate and produce a\n\nknowledgeable witness on Deposition Topics 1\u20135 within thirty (30) days of the Court\u2019s order.\n\n\n\n\n 10\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 15 of 16\n\n\n\n\nDated: August 18, 2026\n\n\n Respectfully submitted,\n\n /s/ Rocco Magni\n Max L. Tribble\n Texas State Bar 20213950\n Brian D. Melton\n Texas State Bar 24010620\n Rocco Magni\n Texas State Bar 24092745\n Samuel Drezdzon\n Texas State Bar 24117374\n SUSMAN GODFREY L.L.P.\n 1000 Louisiana\n Suite 5100\n Houston, TX 77002\n Telephone: (713) 651-9366\n Facsimile: (713) 654-6666\n mtribble@susmangodfrey.com\n bmelton@susmangodfrey.com\n rmagni@susmangodfrey.com\n sdrezdzon@susmangodfrey.com\n\n Tamar Lusztig\n NY State Bar 5125174\n Emily Portuguese\n NY State Bar 5920327\n One Manhattan West, 50th Floor\n New York, NY 10001\n tlusztig@susmangodfrey.com\n eportuguese@susmangodfrey.com\n\n Tanner Laiche\n WA State Bar 60450\n 401 Union Street, Suite 3000\n Seattle, WA 98101\n tlaiche@susmangodfrey.com\n\n Attorneys for Petitioner Neural AI, LLC\n\n\n\n\n 11\n\f Case 7:26-mc-00324 Document 1 Filed 08/18/26 Page 16 of 16\n\n\n\n\n CERTIFICATE OF SERVICE\n\n The undersigned does hereby certify that on August 18, 2026, a true and correct copy of\n\nthe foregoing document was served on counsel for Google, LLC and all counsel of record in the\n\nunderlying action.\n\n\n /s/ Rocco Magni\n Rocco Magni\n\n\n\n CERTIFICATE OF CONFERENCE\n\n The undersigned certifies that counsel for Neural AI, LLC conferred in good faith with\n\ncounsel for non-party Google, LLC regarding the issues raised in this Motion, including Zoom\n\nconferences on or about July 25, August 1, and August 17, 2026, and related email correspondence.\n\nDespite those efforts, the parties were unable to resolve the dispute.\n\n /s/ Rocco Magni\n Rocco Magni\n\n\n\n\n 12\n\f","ocr_status":2,"date_upload":"2026-08-19T03:49:27.198041-07:00","document_number":"1","attachment_number":null,"pacer_doc_id":"181037219895","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Compel","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514514/","id":490514514,"tags":[],"absolute_url":"/docket/74667129/1/1/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:12.960097-07:00","date_modified":"2026-08-23T05:58:25.868434-07:00","sha1":"60e53d41c996581f8dfcb1bdebc27aa96d7d9a84","page_count":5,"file_size":174549,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.1.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.1.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":" Case 7:26-mc-00324 Document 1-1 Filed 08/18/26 Page 1 of 5\n\n\n\n\n IN THE UNITED STATES DISTRICT COURT\n FOR THE WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\n\n NEURAL AI, LLC,\n Misc. Case No. 7:26-mc-324\n Petitioner,\n Principal case pending in Western District of\n v. Texas, Civil Action No. 7:24-cv-00221-LS-\n DTG\n GOOGLE, LLC,\n\n Respondent.\n\n\n DECLARATION OF TANNER LAICHE IN SUPPORT OF NEURAL AI\u2019S\n MOTION TO COMPEL COMPLIANCE WITH SUBPOENA\n SERVED ON THIRD-PARTY GOOGLE, LLC\n\n I, Tanner Laiche, declare as follows:\n\n 1. I am an attorney duly licensed to practice in the States of California and Washington\n\nand am admitted to the Western District of Texas. I am an associate at the law firm of Susman\n\nGodfrey LLP, and am a counsel of record for Petitioner Neural AI, LLC (\u201cNAI\u201d) in the above-\n\ncaptioned matter. I make this declaration in support of NAI\u2019s Motion to Compel Compliance with\n\nSubpoena Served on Third-Party Google, LLC (\u201cGoogle\u201d). Unless otherwise stated, I have\n\npersonal knowledge of the facts set forth herein and could competently testify thereto.\n\n 2. Attached hereto as Exhibit 1 is a true and correct copy of NAI\u2019s First Amended\n\nComplaint for Patent Infringement filed in the Underlying Action on December 12, 2024.\n\n 3. Attached hereto as Exhibit 2 is a true and correct copy of U.S. Patent No.\n\n8,648,867, entitled \u201cGraphic Processor Based Accelerator System and Method.\u201d\n\n 4. Attached hereto as Exhibit 3 is a true and correct copy of Reissue Patent No.\n\nRE48,438, entitled \u201cGraphic Processor Based Accelerator System and Method.\u201d\n\n\n\n\n 1\n\f Case 7:26-mc-00324 Document 1-1 Filed 08/18/26 Page 2 of 5\n\n\n\n\n 5. Attached hereto as Exhibit 4 is a true and correct copy of Reissue Patent No.\n\nRE49,461, entitled \u201cGraphic Processor Based Accelerator System and Method.\u201d\n\n 6. Attached hereto as Exhibit 5 is a true and correct copy of NAI\u2019s Subpoenas to\n\nProduce Documents and to Testify at a Deposition served on Google, LLC, served on June 25,\n\n2026, including the accompanying definitions, instructions, requests for production, and\n\ndeposition topics.\n\n 7. Attached hereto as Exhibit 6 is a true and correct copy of the Affidavit of Service\n\nconfirming service of the subpoenas on Google\u2019s registered agent on June 25, 2026.\n\n 8. Attached hereto as Exhibit 7 is a true and correct copy of NAI\u2019s January 20, 2026\n\nFinal Infringement Contentions Cover Page filed in the Underlying Action.\n\n 9. Attached hereto as Exhibit 8 is a true and correct copy of NVIDIA\u2019s Amended\n\nAnswer to NAI\u2019s Amended Complaint, filed on November 25, 2025, as docketed at Dkt. 130 in\n\nthe Underlying Action (public, redacted version).\n\n 10. Attached hereto as Exhibit 9 is a true and correct copy of Nonparty Google LLC\u2019s\n\nObjections and Responses to Neural AI, LLC\u2019s Subpoena to Produce Documents, Information, or\n\nObjects, dated July 21, 2026.\n\n 11. Attached hereto as Exhibit 10 is a true and correct copy of Responses and\n\nObjections of Nonparty Google LLC to Subpoena to Testify at a Deposition in a Civil Action,\n\ndated July 21, 2026.\n\n 12. Attached hereto as Exhibit 11 is a true and correct copy of the email\n\ncorrespondence between counsel for NAI and counsel for Google regarding the extension of time\n\nfor Google to serve its responses and objections.\n\n 13. Attached hereto as Exhibit 12 is a true and correct copy of the meet-and-confer\n\n\n\n\n 2\n\f Case 7:26-mc-00324 Document 1-1 Filed 08/18/26 Page 3 of 5\n\n\n\n\ncorrespondence between counsel for NAI and counsel for Google.\n\n 14. Attached hereto as Exhibit 13 is a true and correct copy of NAI\u2019s Third-Party\n\nQuestions provided to Google on August 4, 2026.\n\n 15. Attached hereto as Exhibit 14 is a true and correct copy of NAI\u2019s Draft Third-Party\n\nDeclaration provided to Google on August 4, 2026.\n\n 16. Attached hereto as Exhibit 15 is a true and correct copy of an NVIDIA Blog post\n\ntitled \u201cNVIDIA and Google Cloud Collaborate to Advance Agentic and Physical AI,\u201d dated April\n\n22, 2026, printed from https://blogs.nvidia.com. I obtained this document from NVIDIA\u2019s publicly\n\naccessible website on August 17, 2026.\n\n 17. Attached hereto as Exhibit 16 is a true and correct copy of the NVIDIA Solutions\n\non Google Cloud webpage, printed from https://cloud.google.com. I obtained this document from\n\nGoogle Cloud\u2019s publicly accessible website on August 17, 2026.\n\n 18. Attached hereto as Exhibit 17 is a true and correct copy of the Google Careers \u2013\n\nAustin webpage, printed from https://careers.google.com. I obtained this document from Google\u2019s\n\npublicly accessible website on August 17, 2026.\n\n 19. Attached hereto as Exhibit 18 is a true and correct copy of a Google blog post titled\n\n\u201cComing soon to the Lone Star State: more office space and a data center,\u201d dated June 14, 2019,\n\nprinted from https://blog.google. I obtained this document from Google\u2019s publicly accessible\n\nwebsite on August 17, 2026.\n\n 20. Attached hereto as Exhibit 19 is a true and correct copy of the Google Office\n\nLocations webpage listing Austin, Texas among Google\u2019s office locations, printed from\n\nhttps://about.google. I obtained this document from Google\u2019s publicly accessible website on\n\nAugust 17, 2026.\n\n\n\n\n 3\n\f Case 7:26-mc-00324 Document 1-1 Filed 08/18/26 Page 4 of 5\n\n\n\n\n 21. Attached hereto as Exhibit 20 is a true and correct copy of the meet-and-confer\n\ncorrespondence between counsel for NAI and counsel for Google from August 5, 2026 through\n\nAugust 18, 2026.\n\n 22. Attached hereto as Exhibit 21 is a true and correct copy of NAI\u2019s revised Draft\n\nThird-Party Declaration provided to Google on August 18, 2026.\n\n 23. The Underlying Action\u2014Neural AI, LLC v. NVIDIA Corporation, Case No. 7:24-\n\ncv-00221-LS-DTG (W.D. Tex.)\u2014is a patent infringement action in which NAI alleges that\n\nNVIDIA Corporation\u2019s (\u201cNVIDIA\u201d) GPU-accelerated computing hardware and software infringe\n\nU.S. Patent No. 8,648,867 (the \u201c\u2019867 Patent\u201d), Reissue Patent No. RE48,438 (the \u201c\u2019438 Patent\u201d),\n\nand Reissue Patent No. RE49,461 (the \u201c\u2019461 Patent\u201d) (collectively, the \u201cAsserted Patents\u201d).\n\n 24. Throughout discovery in the above-captioned action, NVIDIA has taken the\n\nposition that NAI must obtain evidence from NVIDIA\u2019s customers and end users to prove how the\n\naccused products are actually deployed and configured. During a sealed discovery conference on\n\nSeptember 8, 2025, NVIDIA\u2019s counsel represented to the Court that it only provides tools for end-\n\nuser companies to build their own AI applications on NVIDIA hardware and that if NAI wanted\n\nto learn how the accused software was deployed in real-world systems, NAI would need to seek\n\nthat information directly from NVIDIA\u2019s customers and end users.\n\n 25. Throughout discovery NVIDIA has also disclaimed knowledge concerning how its\n\ncustomers, partners, and end users ultimately deploy, configure, and operate NVIDIA hardware\n\nand software. NAI accordingly turned to third-party discovery, including subpoenas to Google, to\n\nobtain the evidence NVIDIA contends NAI must have.\n\n 26. As of the date of this declaration, Google has not: (a) identified any specific\n\ndocument requests to which it will respond; (b) agreed to produce any responsive documents;\n\n\n\n\n 4\n\f Case 7:26-mc-00324 Document 1-1 Filed 08/18/26 Page 5 of 5\n\n\n\n\n(c) answered NAI\u2019s technical questions; (d) proposed any revisions to the draft declaration;\n\n(e) designated a witness for deposition; or (f) committed to any date by which it will do any of the\n\nforegoing.\n\n 27. Document discovery in the Underlying Action closed on August 11, 2026.\n\nDefendant NVIDIA in the underlying action stipulated to extend the deadline for third-party\n\nmotions to compel to August 18, 2026. Deposition discovery closes on September 16, 2026.\n\n I declare under penalty of perjury under the laws of the United States of America that the\n\nforegoing is true and correct.\n\n Executed on August 18, 2026, in Seattle, Washington.\n\n\n\n\n Tanner Laiche\n\n\n\n\n 5\n\f","ocr_status":2,"date_upload":"2026-08-19T03:49:28.804767-07:00","document_number":"1","attachment_number":1,"pacer_doc_id":"181037219896","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Affidavit of Tanner Laiche","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514515/","id":490514515,"tags":[],"absolute_url":"/docket/74667129/1/2/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:12.984702-07:00","date_modified":"2026-08-23T02:41:24.100090-07:00","sha1":"a6b27b6d318e6d5f21268e0aa212239f07c871a4","page_count":95,"file_size":2296844,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.2.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.2.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-2 Filed 08/18/26 Page 1 of 95\n\n\n\n\n EXHIBIT\n\n 1\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 2 of1 95\n of 94\n\n\n\n\n UNITED STATES DISTRICT COURT\n FOR THE WESTERN DISTRICT OF TEXAS\n MIDLAND-ODESSA DIVISION\n\nNEURAL AI, LLC )\n )\n )\n Plaintiff, )\nv. ) Civil Action No. 7:24-cv-00221\n )\nNVIDIA CORPORATION )\n ) JURY TRIAL DEMANDED\n )\n Defendant. )\n )\n\n FIRST AMENDED COMPLAINT FOR PATENT INFRINGEMENT\n\n Neural AI, LLC (\u201cNeural AI\u201d or \u201cPlaintiff\u201d) alleges against Defendant Nvidia Corporation\n\n(\u201cNvidia\u201d or \u201cDefendant\u201d) the following:\n\n 1. This case involves patented technologies that revolutionized, and have become\n\nwidely adopted in, the field of graphical processor unit (\u201cGPU\u201d)-accelerated computing for\n\nartificial intelligence, machine learning, and complex numerical simulations. GPU-accelerated\n\ncomputing powers many of the most advanced and powerful forms of artificial intelligence that\n\nhave exploded over the past decade.\n\n 2. Highly complex numerical simulations, such as the prediction of protein chains,\n\ngenetic sequences and cryptographic sequences, and advanced machine learning techniques such\n\nas deep learning neural networks, require hardware capable of a high degree of parallel processing\n\nfor efficient computation. GPUs, which generally have hundreds to thousands more computational\n\nprocessors or \u201ccores\u201d than central processing units (\u201cCPUs\u201d), are the preferred hardware for\n\nexecuting such simulations and machine learning techniques. Indeed, the parallel operation of\n\nthousands of high-performance GPUs have become a basic necessity for the execution and training\n\n\n\n\n 1\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 3 of2 95\n of 94\n\n\n\n\nof complex natural language and image-generation models, such as ChatGPT\u2019s GPT-4 and\n\nSora.AI. (See https://www.fierceelectronics.com/sensors/chatgpt-runs-10k-nvidia-training-gpus-\n\npotential-thousands-more.)\n\n 3. Before Plaintiff\u2019s innovations, the conventional wisdom in the field of GPU-\n\naccelerated computing was that the exchange of intermediate outputs between a GPU and a CPU\n\nwas too computationally expensive. This was so because the GPU, adapted for highly parallel\n\nprocessing tasks (e.g., graphically modeling a physics engine or rendering complex moving\n\nimages), was ill-suited for handling operations better left to the CPU, like interacting with a user\u2019s\n\nmouse and keyboard or sending and receiving simple datasets. Plaintiff\u2019s foundational technology\n\nchanged this by inventing techniques that leveraged the unique advantages of both the CPU and\n\nthe GPU to enable their efficient interplay in hardware-accelerated computing.\n\n 4. Plaintiff\u2019s patented technologies are enshrined in U.S. Patent Nos. 8,648,867 (\u201cthe\n\n\u2019867 Patent\u201d), RE49,461 (\u201cthe \u2019461 Patent\u201d), and RE48,438 (\u201cthe \u2019438 Patent\u201d) (collectively, \u201cthe\n\nAsserted Patents\u201d or \u201cThe GPU-Based Acceleration Patents\u201d).\n\n NATURE OF THE CASE\n\n 5. Plaintiff brings claims under the patent laws of the United States, 35 U.S.C. \u00a7 1, et\n\nseq., for infringement of the Asserted Patents. Defendant has infringed and continues to infringe\n\neach of the Asserted Patents under at least 35 U.S.C. \u00a7\u00a7271(a), 271(b) and 271(c).\n\n THE PARTIES\n\n 6. Plaintiff Neural AI, LLC, is the owner by assignment of each of the Asserted\n\nPatents.\n\n 7. The technology of the Asserted Patents underpins multiple artificial intelligence\n\nand accelerated computing products that incorporate the patented technology, such as Neurala,\n\n\n\n\n 2\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 4 of3 95\n of 94\n\n\n\n\nInc.\u2019s Vision Inspection Automation (VIA), Vision AI software, and Brain Builder platform.\n\n 8. Neural AI is a Texas limited liability company and is a registered business in Texas.\n\nNeural AI maintains its principal office in this District, at 510 Austin Avenue, Suite 2554, Waco,\n\nTX 76701.\n\n 9. Defendant Nvidia Corporation is a Delaware corporation with its headquarters and\n\nprincipal place of business in Santa Clara, California. (See https://investor.nvidia.com/financial-\n\ninfo/sec-filings/sec-filings-details/default.aspx?FilingId=17293267, U.S. Securities and Exchange\n\nCommission Form 10-K for Fiscal Year Ended January 28, 2024;\n\nhttps://nvidianews.nvidia.com/multimedia/santa-clara-headquarters.) Defendant Nvidia\n\nCorporation is registered with the Secretary of State to conduct business in Texas. Nvidia has an\n\noffice in this District located in Austin, Texas. (See https://www.nvidia.com/en-us/contac.)\n\n JURISDICTION & VENUE\n\n 10. This action arises under the Patent Laws of the United States, 35 U.S.C. \u00a7 1, et seq.\n\nThe Court has subject matter jurisdiction pursuant to 28 U.S.C. \u00a7\u00a7 1331 and 1338(a).\n\n 11. This Court has personal jurisdiction over Defendant because it regularly conducts\n\nbusiness in the State of Texas and in this District. This business includes operating systems, using\n\nand/or providing computer hardware, software, firmware, and platforms, and/or providing services\n\nand/or engaging in activities in Texas and in this District that infringe one or more claims of the\n\nAsserted Patents, as well as inducing and contributing to the direct infringement of others through\n\nacts in this District.\n\n 12. Nvidia has also, directly and through its extensive network of partnerships,\n\nincluding with local IT service providers, purposefully and voluntarily placed products and/or\n\nprovided services that practice and/or implement the methods, systems, and apparatuses claimed\n\n\n\n\n 3\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 5 of4 95\n of 94\n\n\n\n\nin the Asserted Patents into the stream of commerce with the intention and expectation that they\n\nwill be purchased and used by customers in this District, as detailed below. (See\n\nhttps://www.nvidia.com/en-us/about-nvidia/partners/.)\n\n 13. Defendant has also acknowledged that this Court has personal jurisdiction over it\n\nin cases filed against it in this District. (See, e.g., Vantage Micro LLC v. NVIDIA Corporation,\n\nCase No. 6:19-cv-00582-RP, ECF 22 (W.D. Tex., Jan. 4, 2020) (admitting to personal\n\njurisdiction); Ocean Semiconductor LLC v. NVIDIA Corporation, Case No. 6:20-cv-01211-ADA,\n\nECF 14 (W.D. Tex., Mar. 12, 2021) (same).) Defendant has admitted \u201cit is subject to this Court\u2019s\n\ngeneral personal jurisdiction.\u201d (Id.)\n\n 14. Venue is proper in this District pursuant to 28 U.S.C. \u00a7\u00a7 1391(b) and (c) and 28\n\nU.S.C. \u00a7 1400(b) because Defendant Nvidia Corporation has regular and systematic contacts\n\nwithin this District and has committed acts of infringement within this District.\n\n 15. Defendant Nvidia Corporation is a registered business in Texas and has regular and\n\nestablished places of business in this District. Nvidia has an office in this District located at 11001\n\nLakeline Blvd, Suite 100 Bldg. 2, Austin, Texas 78717. (See https://craft.co/nvidia.) Nvidia\u2019s\n\nAustin office has \u201c54,000 SF of new shell office and DVS labs\u201d and \u201c35,000 SF of offices, testing\n\nand software labs.\u201d (See https://kiddgrp.com/project/nvidia-corporation/.)\n\n 16. Defendant Nvidia Corporation has hundreds of employees in this District\u2014\n\nincluding positions in engineering, sales, marketing, and finance. LinkedIn lists approximately 792\n\npersons associated with Nvidia and identified as being located in the Austin or Austin metropolitan\n\narea. (See\n\nhttps://www.linkedin.com/company/nvidia/people/?facetGeoRegion=104472865%2C90000064.)\n\nLinkedIn also lists approximately 1,158 persons associated with Nvidia and identified as being\n\n\n\n\n 4\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 6 of5 95\n of 94\n\n\n\n\nlocated in the State of Texas. (See id.)\n\n 17. In addition, Defendant Nvidia Corporation has over 100 jobs posted for the State\n\nof Texas on its affiliated Workday page with approximately 93 of those jobs\u2014the vast majority of\n\nwhich are engineering jobs\u2014listed for Austin, Texas. (See\n\nhttps://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite?locations=91336993fab910\n\naf6d702939a7fcc2d9&locations=91336993fab910af6d702b631b94c2de (approximately 111\n\nNvidia job postings for Texas).) These jobs are particularly relevant to the Asserted Patents and\n\nAccused Products, as defined below, because they pertain to artificial intelligence, machine\n\nlearning, deep learning, data centers, accelerated computing, high performance computing\n\n(\u201cHPC\u201d), and related hardware, software, and/or firmware\u2014including Nvidia\u2019s GPUs, CPUs,\n\nsystems-on-a-chip (\u201cSoCs\u201d), platforms, and application programming interfaces.\n\n 18. Nvidia\u2019s operations in this District include client outreach and sales for each of the\n\nAccused Products and related or supporting services. As detailed above, Nvidia has customer-\n\nfacing personnel and operations in this District. Nvidia also provides technical support to partners\n\nand customers for its products in the District.\n\n 19. Nvidia has committed acts of infringement within this District. Nvidia uses the\n\nAccused Products in this District in manners that practice the Asserted Patents, including by testing\n\nthe Accused Products and by using the Accused Products at its offices and premises in this District.\n\n 20. Defendant makes, uses, advertises, offers for sale, and/or sells hardware for\n\naccelerated computing, including GPUs, CPUs, and SoCs; computers for accelerated computing\n\n(e.g., supercomputers, servers, and data centers for high performance computing); and computer\n\nplatform software-as-a-service (\u201cSaaS\u201d) that implements accelerated computing (including the\n\nAccused Products) in the State of Texas and in this District directly and/or through its partnerships\n\n\n\n\n 5\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 7 of6 95\n of 94\n\n\n\n\nwith businesses in the State of Texas and in this District. Defendant also provides data center and\n\nHPC services that practice the Asserted Patents in the State of Texas and in this District directly\n\nand/or through its partnerships with businesses in the State of Texas and in this District.\n\n 21. Nvidia sells, offers for sale, advertises, makes, installs, and/or otherwise provides\n\nhardware, software, firmware, and/or computer platforms for accelerated computing and data\n\ncenter and HPC services, including the Accused Products, the use of which infringes the Asserted\n\nPatents in this District and the State of Texas. (See https://www.nvidia.com/en-us/data-\n\ncenter/solutions/accelerated-computing/.) Nvidia performs these acts directly and/or through its\n\npartnerships with other entities. (See id. (\u201cNVIDIA has defined a range of accelerated platforms\n\nthat each consist of hardware systems designed according to the needs of the use case as well as\n\nthe software stack that enables the operation and management of the business applications. These\n\nhardware systems and software are available from NVIDIA and our partners.\u201d).)\n\n 22. Nvidia also uses a network of partners, which comprise re-sellers, managed service\n\nproviders, and product and solution experts, to provide the Accused Products and implementation\n\nservices for the Accused Products to customers in this District. Each of these partners sells, offers\n\nfor sale, installs, and/or implements Nvidia\u2019s accelerated computing hardware, software, and/or\n\ncomputer platform services. (See https://www.nvidia.com/en-us/about-nvidia/partners/.)\n\n 23. Nvidia\u2019s partners include \u201cData Center Provider[s].\u201d (See\n\nhttps://www.nvidia.com/en-us/about-nvidia/partners/.) Nvidia\u2019s Data Center Provider partners\n\n\u201coffer colocation services such as high-density data center facilities, interconnected infrastructure,\n\nand state-of-art cooling technologies for hosting NVIDIA DGX\u2122 servers globally.\u201d (See id.)\n\nNvidia\u2019s Data Center Provider partners in the \u201cNVIDIA DGX-Ready Data Center program, built\n\non the NVIDIA DGX\u2122 platform and delivered by NVIDIA partners,\u201d help \u201caccelerate the scaling\n\n\n\n\n 6\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 8 of7 95\n of 94\n\n\n\n\nof AI across [a customer\u2019s] organization.\u201d (See https://www.nvidia.com/en-us/data-\n\ncenter/colocation-partners/#aligned-energy.)\n\n 24. As further detailed below, Nvidia engages in activities that directly infringe the\n\nAsserted Patents within this District. For example, Nvidia\u2019s operation and use of its accelerated\n\ncomputing hardware, software, and/or computer platform services, including its data center-scale\n\naccelerated computing platforms, within this District infringe the Asserted Patents.\n\n 25. Nvidia also infringes (directly or indirectly) the Asserted Patents by providing\n\nservices in connection with the Accused Products including installing, maintaining, supporting,\n\noperating, providing instructions, and/or advertising Nvidia\u2019s computer platform, data center, and\n\nHPC services within this District. For example, under Nvidia\u2019s cloud and data center line of\n\nproducts and services, the Nvidia DGX platform is a \u201ca fully integrated hardware and software AI\n\nplatform\u201d and \u201ccombines the best of NVIDIA software, infrastructure, and expertise in a modern,\n\nunified AI development solution.\u201d (See https://www.nvidia.com/en-us/data-center/dgx-platform/.)\n\nIndeed, \u201cDGX infrastructure is a complete AI solution, and includes NVIDIA AI Enterprise\n\nsoftware to accelerate data science pipelines and streamline development and deployment of\n\nproduction-grade AI applications.\u201d (See id.) Nvidia platform user and partner customers infringe\n\nthe Asserted Patents by installing and operating Nvidia\u2019s computer platform software, which\n\nperforms the claimed methods in the Asserted Patents within this District. (See also, e.g.,\n\nhttps://www.nvidia.com/en-us/data-center/products/ai-enterprise/ (Nvidia AI Enterprise);\n\nhttps://developer.nvidia.com/cuda-zone (Nvidia CUDA Toolkit); https://www.nvidia.com/en-\n\nus/data-center/gpu-cloud-computing/ (GPU Cloud Computing).)\n\n 26. Defendant encourages and induces its customers of the Accused Products to\n\nperform the methods claimed in the Asserted Patents. For example, Nvidia makes its accelerated\n\n\n\n\n 7\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 9 of8 95\n of 94\n\n\n\n\ncomputing platforms and services available on its website, widely advertises those platforms and\n\nservices, provides applications that allow partners and users to access those platforms and services,\n\nprovides instructions for installing, and maintaining those platforms and services and supporting\n\nsoftware and/or firmware, and provides technical support to users. (See\n\nhttps://www.nvidia.com/en-us/data-center/dgx-support/.)\n\n 27. Nvidia further encourages and induces its customers to operate Nvidia\u2019s hardware\n\nand software in an infringing manner, and to use Nvidia\u2019s infringing computer platforms, by\n\nproviding directions for and encouraging customers to install software, such as software for\n\nNVIDIA AI Enterprise and CUDA, (see https://docs.nvidia.com/ai-enterprise/deployment-guide-\n\nvmware/0.1.0/software.html; https://developer.nvidia.com/cuda-downloads), which offers\n\nevaluation, installation, configuration, customization, and development of Nvidia\u2019s infringing\n\nsoftware products and services.\n\n 28. Defendant also contributes to the infringement of its customers and end users of the\n\nAccused Products by offering within the United States or importing into the United States the\n\nAccused Products, which are for use in practicing, and under normal operation practice, one or\n\nmore of the methods claimed in the Asserted Patents, constituting a material part of the inventions\n\nclaimed, and not a staple article or commodity of commerce suitable for substantial non-infringing\n\nuses. Indeed, as shown herein, the Accused Products and the example functionality described\n\nbelow have no substantial non-infringing uses and are specifically designed to practice the methods\n\nclaimed in the Asserted Patents.\n\n 29. On information and belief, Defendant has not disputed that venue is proper in this\n\nDistrict in cases filed against it in this District. (See, e.g., Vantage Micro LLC v. NVIDIA Corp.,\n\nNo. 6:19-cv-00582, ECF 22; Polaris Innovations Ltd. v. Dell Inc. et al., No. 5:16-cv-00451, ECF\n\n\n\n\n 8\n\f Case\n Case7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30Filed\n Filed\n 08/18/26\n 12/12/24Page\n Page\n 10 of\n 9 of\n 9594\n\n\n\n\n19; Cirrus Logic, Inc. v. ATI Techs., et al., No. 1:03-cv-00302, ECF 6.)\n\n 30. Defendant\u2019s infringement adversely impacts Plaintiff in this District.\n\n PLAINTIFF\u2019S PATENTED INNOVATIONS\n\n 31. The Asserted Patents pioneered the adaptation of GPU-acceleration technology to\n\nthe supervised execution of complex artificial intelligence algorithms and numerical simulations,\n\nsuch that it became possible for the first time to dynamically supervise, review, and correct\n\nintermediate \u201csolutions\u201d that were produced by these accelerated algorithms and simulations\n\nwithout performance loss.\n\n The GPU-Based Acceleration Patents\n U.S. Patent Nos. 8,648,867, RE49,461, and RE48,438\n\n 32. The \u2019867, \u2019461, and \u2019438 Patents are part of the same patent family and generally\n\ndisclose and claim systems and methods related to the accelerated execution of numerical\n\nsimulations and neural networks such that the intermediate outputs of a given execution \u201cstep\u201d can\n\nbe dynamically transferred from the GPU to the CPU, reviewed, and corrected within the same\n\ncomputational cycle before being fed as inputs to the next execution step.\n\n 33. The \u2019867 Patent is entitled \u201cGraphic Processor Based Accelerator System and\n\nMethod,\u201d was filed on September 24, 2007, and was duly and legally issued by the United States\n\nPatent and Trademark Office (\u201cUSPTO\u201d) on February 11, 2014. The \u2019867 Patent claims priority\n\nto Provisional Application No. 60/826,892, filed on September 25, 2006. A true and correct copy\n\nof the \u2019867 Patent is attached as Exhibit 1.\n\n 34. The \u2019438 Patent is entitled \u201cGraphic Processor Based Accelerator System and\n\nMethod,\u201d was filed on November 9, 2017, and was duly and legally issued by the USPTO on\n\nFebruary 16, 2021. The \u2019438 Patent is a re-issue of the \u2019867 Patent and claims priority to\n\nProvisional Application No. 60/826,892, filed on September 25, 2006. A true and correct copy of\n\n\n\n 9\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 11 10\n of 95\n of 94\n\n\n\n\nthe \u2019438 Patent is attached as Exhibit 2.\n\n 35. The \u2019461 Patent is also entitled \u201cGraphic Processor Based Accelerator System and\n\nMethod,\u201d was filed on December 29, 2020, and was duly and legally issued by the USPTO on\n\nMarch 14, 2023. The \u2019461 Patent is a re-issue of the \u2019867 Patent and claims priority to Provisional\n\nApplication No. 60/826,892, filed on September 25, 2006. A true and correct copy of the \u2019461\n\nPatent is attached as Exhibit 3.\n\n 36. The \u2019867 Patent improves upon prior GPU acceleration technology by disclosing\n\nand claiming a novel hardware and firmware system for performing a numerical simulation that\n\npermits dynamic editing of the outputs that flow from intermediate \u201csteps\u201d of that simulation,\n\nbefore they become inputs to the next \u201cstep.\u201d In particular, the \u2019867 patent discloses a CPU tethered\n\nto a GPU-based accelerator, each with their own corresponding memories, and an accelerator\n\n\u201ccontroller\u201d that coordinates transfers of data between the CPU and the GPU-based accelerator,\n\nsuch that the intermediate results from one step can be transferred from the GPU-based accelerator\n\nto the CPU, reviewed and corrected by the CPU, and transferred back to the GPU-based accelerator\n\nbefore the next computational cycle begins.\n\n 37. The \u2019867 Patent explains that performing the numerical computation in this\n\nstepwise fashion enables the system to eliminate \u201crace conditions,\u201d i.e., conflicts that occur when\n\ntwo programmatic \u201cthreads\u201d attempt to change the same shared data at the same time, which would\n\notherwise occur when other system elements attempt to access intermediate outputs of the\n\nnumerical computation. (See \u2019867 Patent, 5:60-6:31.) This avoids the computational overhead\n\nprevalent in conventional GPU-based accelerator architectures when transferring data from the\n\naccelerator to the CPU.\n\n\n\n\n 10\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 12 11\n of 95\n of 94\n\n\n\n\n 38. By enabling such \u201ccontroller-driven data exchange\u201d between the GPU-based\n\naccelerator and the CPU, the system described in the \u2019867 Patent allows for an \u201cinput parser\u201d\n\nexecuting on a CPU core to \u201cchange input\u2026on the fly during the simulation,\u201d thus enabling\n\nautomatic review and dynamic error correction of the numerical simulations or neural networks\n\nthat are being executed on the claimed system. (See id., 9:8-17.) Such dynamic, in-execution\n\nreview and error correction of whether each intermediate \u201cstep\u201d of a simulation or neural network\n\nis generating correct results is essential to the performance and reliability of large language models,\n\nimage classification, and image generation models that have become prevalent today. Because of\n\nthe scale to which such simulations and models have grown, it is no longer feasible to \u201crestart\u201d\n\nthem from scratch, only to correct them as they execute.\n\n 39. The \u2019461 and \u2019438 Patents disclose hardware and firmware configurations similar\n\nto those of the \u2019867 Patent, but are directed to using those configurations to process the layers of\n\nan artificial neural network (\u201cANN\u201d). The \u2019461 Patent is directed to further interplay between the\n\nCPU and the GPU-based accelerator: separating the CPU and GPU-based accelerator into separate\n\n\u201cstreams,\u201d whereby the CPU executes a \u201cuser interaction stream\u201d (e.g., enabling the parsing and\n\ndynamic editing of intermediate outputs, or for the ANN to be paused and resumed), while the\n\naccelerator executes a \u201ccomputational stream\u201d that executes the layers of the artificial neural\n\nnetwork. When the ANN is initialized, control over the generation of outputs shifts to the\n\ncomputational stream. However, once a pre-defined layer of the ANN has completed execution,\n\nor is interrupted, control over the generation of outputs and feeding of inputs is shifted back to the\n\nCPU\u2019s user interaction stream.\n\n 40. The Asserted Patents describe this \u201cshift of priorities\u201d as \u201c[t]he crucial feature of\n\nthe interaction between the User Interaction Stream and the Computational Stream.\u201d (\u2019867 Patent,\n\n\n\n\n 11\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 13 12\n of 95\n of 94\n\n\n\n\n7:45-47.) Even though the computational stream is in control during the ANN computation,\n\npriority shifting enables \u201c[t]he user [to] retain[] the ability to interrupt the simulation, change the\n\ninput, or to change the display properties of the framework\u201d because the user\u2019s \u201cinteractions are\n\nqueued to be performed at times determined by the controller-driven data exchange to avoid\n\ncorruption of the data.\u201d (Id., 8:47-57.)\n\n ACCUSED PRODUCTS\n\n 41. Nvidia offers, sells, and uses several products that provide and implement GPU-\n\nacceleration hardware, software, platforms, and services for individuals and enterprises and\n\nincorporate Plaintiff\u2019s patented technologies. (See https://www.nvidia.com/en-\n\nus/solutions/ai/inference/; https://marketplace.nvidia.com/en-us/data-center/?page=4;\n\nhttps://marketplace.nvidia.com/en-us/laptops-workstations/?page=9;\n\nhttps://marketplace.nvidia.com/en-us/software/?page=3.)\n\n 42. The Accused Products include Nvidia\u2019s GPU accelerators and superchips. (See\n\nhttps://resources.nvidia.com/l/en-us-gpu.) Nvidia\u2019s GPU accelerators include Nvidia\u2019s GPUs with\n\nNvidia\u2019s \u201cHopper,\u201d \u201cAda Lovelace,\u201d \u201cAmpere,\u201d \u201cTuring,\u201d \u201cVolta,\u201d \u201cPascal,\u201d and \u201cMaxwell\u201d\n\nGPU architectures. (See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-896/support-\n\nmatrix/index.html.) These GPUs are specifically designed to run and implement GPU-based\n\nhardware acceleration using Nvidia\u2019s proprietary CUDA (Compute Unified Device Architecture)\n\nplatform and CUDA libraries for GPU acceleration. (See id. (Nvidia GPU architectures\n\nimplementing Nvidia\u2019s cuDNN (CUDA Deep Neural Network) library for GPU acceleration.);\n\nhttps://developer.nvidia.com/cuda-gpus.)\n\n 43. Nvidia\u2019s Hopper GPUs include the H100 and H200 GPUs. (See\n\nhttps://www.nvidia.com/en-us/data-center/technologies/hopper-architecture/ (Hopper\n\n\n\n\n 12\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 14 13\n of 95\n of 94\n\n\n\n\narchitecture); https://www.nvidia.com/en-us/data-center/h100/ (H100);\n\nhttps://www.nvidia.com/en-us/data-center/h200/ (H200).) In addition, Nvidia\u2019s superchips that\n\nimplement GPU accelerators include the GH200, or Grace Hopper Superchip, which implements\n\nthe Hopper-GPU architecture. (See https://www.nvidia.com/en-us/data-center/grace-hopper-\n\nsuperchip/ (GH200).)\n\n 44. Nvidia\u2019s Ada Lovelace (or Lovelace) GPUs include Nvidia Data Center GPUs,\n\nincluding L40, L40S, and L4 GPUs; Nvidia Workstation and Professional Laptop GPUs, including\n\nRTX Ada Generations series GPUs and Laptop GPUs; and GeForce RTX 40 series GPUs and\n\nLaptop GPUs. (See https://www.nvidia.com/en-us/technologies/ada-architecture/ (Ada Lovelace\n\narchitecture). See https://www.nvidia.com/en-us/data-center/l40/ (L40);\n\nhttps://www.nvidia.com/en-us/data-center/l40s/ (L40S); https://www.nvidia.com/en-us/data-\n\ncenter/l4/ (L4). See https://resources.nvidia.com/en-us-design-viz-stories-ep/l40-linecard (Nvidia\n\nProfessional GPUs); https://www.nvidia.com/en-us/ai-on-rtx/ (RTX GPUs featuring \u201cAccelerated\n\nDevelopment\u201d); https://www.nvidia.com/en-us/design-visualization/desktop-graphics/ (RTX Ada\n\nGeneration GPUs); https://www.nvidia.com/en-us/design-visualization/rtx-professional-\n\nlaptops/compare-table/ (RTX Ada Generation Laptop GPUs). See https://www.nvidia.com/en-\n\nus/geforce/graphics-cards/40-series/ (GeForce RTX 40 GPUs); https://www.nvidia.com/en-\n\nus/geforce/graphics-cards/compare/ (GeForce RTX 40 GPUs); https://www.nvidia.com/en-\n\nus/geforce/laptops/compare/ (GeForce RTX 40 Laptop GPUs).)\n\n 45. Nvidia\u2019s Ampere GPUs include Nvidia Data Center GPUs, including A100, A40,\n\nA30, A16, A10, and A2 GPUs; Nvidia Workstation and Professional Laptop GPUs, including\n\nRTX A series GPUs and Laptop GPUs; GeForce RTX 30 series GPUs and Laptop GPUs; and\n\nGeForce MX570 Laptop GPU. (See https://www.nvidia.com/en-us/data-center/ampere-\n\n\n\n\n 13\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 15 14\n of 95\n of 94\n\n\n\n\narchitecture/ (Ampere architecture). See https://www.nvidia.com/en-us/data-center/a100/ (A100);\n\nhttps://www.nvidia.com/en-us/data-center/a40/ (A40); https://www.nvidia.com/en-us/data-\n\ncenter/a30/ (A30); https://www.nvidia.com/en-us/data-center/a16/ (A16);\n\nhttps://www.nvidia.com/en-us/data-center/a10/ (A10); https://www.nvidia.com/en-us/data-\n\ncenter/a2/ (A2). See https://www.nvidia.com/en-us/design-visualization/desktop-graphics/ (RTX\n\nA GPUs); https://www.nvidia.com/en-us/design-visualization/rtx-professional-laptops/compare-\n\ntable/ (RTX A Laptop GPUs). See https://www.nvidia.com/en-us/geforce/graphics-cards/30-\n\nseries/ (GeForce RTX 30 GPUs); https://www.nvidia.com/en-us/geforce/graphics-cards/compare/\n\n(GeForce RTX 30 GPUs); https://www.nvidia.com/en-us/geforce/laptops/compare/30-series/\n\n(GeForce RTX 30 Laptop GPUs); https://www.nvidia.com/en-us/geforce/gaming-laptops/mx-\n\n570/ (GeForce MX570 Laptop GPU).)\n\n 46. Nvidia\u2019s Turing GPUs include Nvidia Data Center GPUs, including Tesla T4 GPUs\n\nand Quadro RTX 8000 (passive) and Quadro RTX 6000 (passive) GPUs; Nvidia Workstation and\n\nProfessional Laptop GPUs, including T series GPUs and Laptop GPUs, Quadro T series Laptop\n\nGPUs, and Quadro RTX series GPUs and Laptop GPUs; Titan series Titan RTX GPU;\n\nGeForce RTX 20 series and GeForce GTX 16 series GPUs and Laptop GPUs; and GeForce\n\nMX550, MX450, and MX430 Laptop GPUs. (See https://www.nvidia.com/en-us/geforce/turing/\n\n(Turing architecture). See https://www.nvidia.com/en-us/data-center/tesla-t4/ (Tesla T4);\n\nhttps://www.nvidia.com/en-gb/design-visualization/quadro-data-center/ (Quadro RTX 8000\n\n(passive) and Quadro RTX 6000 (passive). See https://www.nvidia.com/en-us/design-\n\nvisualization/quadro/ (T series GPUs/Laptop GPUs, Quadro T series Laptop GPUs, and Quadro\n\nRTX GPUs/Laptop GPUs); https://www.nvidia.com/en-us/design-visualization/desktop-graphics\n\n(T series GPUs/Laptop GPUs); https://www.nvidia.com/content/dam/en-\n\n\n\n\n 14\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 16 15\n of 95\n of 94\n\n\n\n\nzz/Solutions/titan/documents/titan-rtx-for-creators-us-nvidia-1011126-r6-web.pdf (Titan RTX);\n\nhttps://www.nvidia.com/en-us/geforce/20-series/ (GeForce RTX 20 GPUs);\n\nhttps://www.nvidia.com/en-us/geforce/graphics-cards/compare/ (GeForce RTX 20 GPUs and\n\nGeForce GTX 16 GPUs); https://www.nvidia.com/en-us/geforce/gaming-laptops/compare-20-\n\nseries/ (GeForce RTX 20 Laptop GPUs); https://www.nvidia.com/en-us/geforce/gaming-\n\nlaptops/compare-16-series/ (GeForce GTX 16 Laptop GPUs); https://www.nvidia.com/en-\n\nus/geforce/gaming-laptops/mx-550/ (GeForce MX550 Laptop GPU); https://www.nvidia.com/en-\n\nus/geforce/gaming-laptops/mx-450/ (GeForce MX450 Laptop GPU);\n\nhttps://wccftech.com/nvidia-geforce-mx450-turing-discrete-notebook-gpu-gddr6-pcie-4/\n\n(GeForce M Laptop GPUs).)\n\n 47. Nvidia\u2019s Volta GPUs include Nvidia Data Center GPUs, including the Tesla V100\n\nGPU; Nvidia Workstation GPUs, including Quadro GV100; and Titan series Titan V GPU. (See\n\nhttps://www.nvidia.com/en-us/data-center/volta-gpu-architecture/ (Volta architecture);\n\nhttps://www.nvidia.com/en-us/data-center/v100/ (Tesla V100);\n\nhttps://www.nvidia.com/content/dam/en-zz/Solutions/design-\n\nvisualization/productspage/quadro/quadro-desktop/quadro-volta-gv100-data-sheet-us-nvidia-\n\n704619-r3-web.pdf (Quadro GV100); https://nvidianews.nvidia.com/news/nvidia-titan-v-\n\ntransforms-the-pc-into-ai-supercomputer (Titan V).)\n\n 48. Nvidia\u2019s Pascal GPUs include Nvidia Data Center GPUs, including Tesla P100,\n\nP40, and P4 GPUs; Nvidia Workstation and Professional Laptop GPUs, including the\n\nQuadro GP100 GPU and Quadro P series GPUs and Laptop GPUs; Titan series Titan Xp and Titan\n\nX GPUs; GeForce GTX 10 series GPUs and Laptop GPUs; and GeForce MX300 series, MX200\n\nseries, and MX150 Laptop GPUs. (See https://developer.nvidia.com/pascal;\n\n\n\n\n 15\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 17 16\n of 95\n of 94\n\n\n\n\nhttps://www.nvidia.com/en-us/data-center/pascal-gpu-architecture/ (Pascal architecture). See\n\nhttps://www.nvidia.com/en-us/data-center/tesla-p100 (Tesla P100);\n\nhttps://developer.nvidia.com/cuda-gpus (Tesla P40 and P4);\n\nhttps://www.nvidia.com/content/dam/en-zz/Solutions/design-\n\nvisualization/productspage/quadro/quadro-desktop/quadro-pascal-gp100-data-sheet-us-nv-\n\n704562-r1.pdf (Quadro GP100); https://www.nvidia.com/en-us/design-visualization/quadro/\n\n(Quadro P series GPUs/Laptop GPUs). See https://www.nvidia.com/content/geforce-\n\ngtx/NVIDIA_TITAN_X_USER_GUIDE_v02.pdf (Titan X);\n\nhttps://www.nvidia.com/content/geforce-gtx/NVIDIA_TITAN_Xp_USER_GUIDE_v02.pdf\n\n(Titan Xp); https://www.nvidia.com/en-us/geforce/10-series/ (GeForce GTX 10);\n\nhttps://www.nvidia.com/en-us/geforce/graphics-cards/compare/ (GeForce GTX 10 GPUs);\n\nhttps://www.nvidia.com/en-us/geforce/news/gfecnt/nvidia-geforce-gtx-10-series-laptops/\n\n(GeForce GTX 10 Laptop GPUs); https://www.nvidia.com/en-us/geforce/gaming-laptops/mx-\n\n350/ (GeForce MX350 Laptop GPU); https://www.nvidia.com/en-us/geforce/gaming-laptops/mx-\n\n330/ (GeForce MX330 Laptop GPU); https://wccftech.com/nvidia-geforce-mx450-turing-\n\ndiscrete-notebook-gpu-gddr6-pcie-4/ (GeForce M Laptop GPUs).)\n\n 49. Nvidia\u2019s Maxwell GPUs include Nvidia Data Center GPUs, including Tesla M60,\n\nM40, and M10 GPUs; Nvidia Workstation and Professional Laptop GPUs, including Quadro M\n\nseries GPUs and Laptop GPUs, the NVS 810 GPU, and Tesla M6 series Laptop GPUs; Titan series\n\nGTX Titan X GPU; GeForce GTX 900 series and GeForce GTX 700 series GPUs and Laptop\n\nGPUs; and GeForce MX130 series and MX110 Laptop GPUs. (See\n\nhttps://developer.nvidia.com/blog/maxwell-most-advanced-cuda-gpu-ever-made/ (Maxwell\n\narchitecture); https://www.nvidia.com/content/dam/en-zz/Solutions/design-\n\n\n\n\n 16\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 18 17\n of 95\n of 94\n\n\n\n\nvisualization/solutions/resources/documents1/nvidia-m60-datasheet.pdf (M60);\n\nhttps://images.nvidia.com/content/tesla/pdf/78071_Tesla_M40_24GB_Print_Datasheet_LR.PDF\n\n(M40); https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/tesla-\n\nm10/pdf/188359-Tesla-M10-DS-NV-Aug19-A4-fnl-Web.pdf (M10);\n\nhttps://www.nvidia.com/en-us/design-visualization/quadro/ (Quadro M GPUs/Laptop GPUs);\n\nhttps://www.nvidia.com/docs/IO/146527/nvs-810-datasheet.pdf (NVS 810);\n\nhttps://images.nvidia.com/content/tesla/pdf/188300-Tesla-M6-DS-Aug19-A4-fnl-Web.pdf (Tesla\n\nM6); https://www.nvidia.com/content/geforce-gtx/GTX_TITAN_X_User_Guide.pdf (GTX Titan\n\nX); https://developer.nvidia.com/maxwell-compute-architecture (GeForce GTX 900 and 700\n\nGPUs/Laptop GPUs); https://wccftech.com/nvidia-geforce-mx450-turing-discrete-notebook-gpu-\n\ngddr6-pcie-4/ (GeForce M Laptop GPUs).)\n\n 50. These GPUs and superchips implement, and are specifically designed for, GPU-\n\nacceleration for artificial intelligence and neural networks. Nvidia\u2019s proprietary CUDA platform\n\nfor parallel computing, which includes GPU-acceleration libraries such as cuDNN (CUDA Deep\n\nNeural Network), is implemented in the Nvidia Hopper, Ada Lovelace, Ampere, Turing, Volta,\n\nPascal, and Maxwell GPU architectures.\n\n\n\n\n 17\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 19 18\n of 95\n of 94\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-896/support-matrix/index.html\n\n(emphasis added).)\n\n 51. The Accused Products further include Nvidia\u2019s supercomputers and servers that\n\nimplement its GPU accelerators and superchips. These supercomputers and servers include: the\n\nEGX line of servers for data centers and edge devices, the HGX line of supercomputers, the DGX\n\nline of supercomputers, and the OVX line of supercomputers. (See https://www.nvidia.com/en-\n\nus/data-center/solutions/accelerated-computing/.)\n\n 52. Nvidia\u2019s \u201cEGX hardware portfolio\u201d includes \u201caccelerators [that] combine the\n\nperformance of NVIDIA Ampere GPUs.\u201d (See https://www.nvidia.com/en-us/data-\n\ncenter/products/egx/; see https://www.nvidia.com/en-us/design-visualization/egx-graphics/.)\n\nNvidia\u2019s HGX \u201cAI supercomputing platform brings together the full power of NVIDIA GPUs,\n\nNVIDIA NVLink\u2122, NVIDIA networking, and fully optimized AI and high-performance\n\ncomputing (HPC) software stacks.\u201d (See https://www.nvidia.com/en-us/data-center/hgx/;\n\nhttps://nvdam.widen.net/s/5kgbjq2v2t/hpc-hgx-h100-datasheet-nvidia-web.) One example\n\n\n 18\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 20 19\n of 95\n of 94\n\n\n\n\nconfiguration includes \u201cfour or eight H200 or H100 GPUs.\u201d (See id.; see\n\nhttps://nvdam.widen.net/s/5kgbjq2v2t/hpc-hgx-h100-datasheet-nvidia-web.) Nvidia\u2019s DGX\n\nsupercomputers include the DGX H200, DGX BasePOD, and DGX SuperPOD with DGX GB200.\n\n(See https://www.nvidia.com/en-us/data-center/dgx-platform/; see also\n\nhttps://www.nvidia.com/en-us/data-center/base-command/; https://resources.nvidia.com/en-us-\n\ndgx-software/nvidia-base-command (DGX Base Command operating system for DGX data\n\ncenters.) And Nvidia\u2019s OVX supercomputers implement \u201cL40S GPUs . . . for both complex AI\n\nand graphics-intensive workloads.\u201d (See https://www.nvidia.com/en-us/data-center/products/ovx/;\n\nsee https://resources.nvidia.com/en-us-ovx/ovx-datasheet.)\n\n 53. The Accused Products further include Nvidia\u2019s software, platforms, and services\n\nfor accelerated computing. These include CUDA, Nvidia AI Enterprise, the DGX Platform, Nvidia\n\nOmniverse, Nvidia Drive, Nvidia Isaac Sim, and Nvidia NGC.\n\n 54. CUDA is Nvidia\u2019s proprietary \u201cparallel computing platform and programming\n\nmodel.\u201d (See https://developer.nvidia.com/cuda-zone.) CUDA is designed to support Nvidia\u2019s\n\nGPU accelerators and superchips and includes software specifically for GPU-acceleration such as\n\nthe cuDNN \u201cGPU-accelerated library.\u201d (See id.; https://developer.nvidia.com/cudnn.) In addition,\n\nNvidia\u2019s CUDA-X, built on top of CUDA, is a collection of \u201cGPU-accelerated microservices and\n\nlibraries for AI.\u201d (See https://www.nvidia.com/en-us/technologies/cuda-x/.) Nvidia also offers the\n\nCUDA Toolkit and SDK Manager for developing GPU-accelerated applications. (See\n\nhttps://developer.nvidia.com/cuda-toolkit; https://developer.nvidia.com/sdk-manager.)\n\n 55. In addition, Nvidia AI Enterprise is Nvidia\u2019s \u201cend-to-end, cloud-native software\n\nplatform\u201d for \u201caccelerat[ing] data science pipelines . . . and other generative AI applications.\u201d (See\n\nhttps://www.nvidia.com/en-us/data-center/products/ai-enterprise/.) It is Nvidia\u2019s \u201c\u2018operating\n\n\n\n\n 19\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 21 20\n of 95\n of 94\n\n\n\n\nsystem\u2019 for enterprise AI.\u201d (See id.)\n\n 56. In addition, Nvidia\u2019s DGX platform is \u201cis a complete AI solution, and includes\n\nNVIDIA AI Enterprise software.\u201d (See https://www.nvidia.com/en-us/data-center/dgx-platform/.)\n\nNvidia DGX Cloud is \u201can AI-training-as-a-service platform which includes cloud-based\n\ninfrastructure and software for AI, customizable pretrained AI models, and access to NVIDIA\n\nexperts.\u201d (See https://d18rn0p25nwr6d.cloudfront.net/CIK-0001045810/1cbe8fe7-e08a-46e3-\n\n8dcc-b429fc06c1a4.pdf, Nvidia U.S. Securities and Exchange Commission Form 10-K for Fiscal\n\nYear Ended January 28, 2024 at 6.)\n\n 57. In addition, Nvidia Omniverse is \u201ca development platform and operating system\n\nfor building virtual world simulation applications, available as a software subscription.\u201d (See\n\nhttps://d18rn0p25nwr6d.cloudfront.net/CIK-0001045810/1cbe8fe7-e08a-46e3-8dcc-\n\nb429fc06c1a4.pdf, Nvidia U.S. Securities and Exchange Commission Form 10-K for Fiscal Year\n\nEnded January 28, 2024 at 6.) Nvidia Omniverse implements software and services \u201cinto existing\n\nsoftware tools and simulation workflows for building AI systems.\u201d (See\n\nhttps://www.nvidia.com/en-us/omniverse/.)\n\n 58. In addition, Nvidia Drive is a platform that \u201cconsists of both the AI infrastructure\n\nand in-vehicle hardware and software\u201d for autonomous vehicles. (See https://www.nvidia.com/en-\n\nus/self-driving-cars/.) \u201cNVIDIA DRIVE Infrastructure encompasses data center hardware,\n\nsoftware, and workflows\u2014both on premises and in NVIDIA DGX Cloud & Omniverse.\u201d (See id.)\n\n 59. In addition, Nvidia Isaac Sim is a platform that enables \u201cdevelopers to design,\n\nsimulate, test, and train AI-based robots and autonomous machines in a physically-based virtual\n\nenvironment.\u201d (See https://developer.nvidia.com/isaac/sim.) It is built on Nvidia Omniverse. (See\n\nid.)\n\n\n\n\n 20\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 22 21\n of 95\n of 94\n\n\n\n\n 60. In addition, Nvidia NGC is a collection of software services and tools that support\n\n\u201cend-to-end AI and digital twin workflows\u201d that runs on \u201cNVIDIA GPU-accelerated platforms.\u201d\n\n(See https://www.nvidia.com/en-us/gpu-cloud/.) NGC \u201coffers a collection of cloud services . . .\n\nfor generative AI, drug discovery, and speech AI solutions, and the NGC Private Registry for\n\nsecurely sharing proprietary AI software.\u201d (See id.)\n\n FIRST CAUSE OF ACTION\n (INFRINGEMENT OF THE \u2019867 PATENT)\n\n 61. Plaintiff realleges and incorporates by reference the allegations of the preceding\n\nparagraphs of this Complaint.\n\n 62. Defendant has infringed and continues to infringe one or more claims of the \u2019867 Patent\n\nin violation of 35 U.S.C. \u00a7 271 in this District and elsewhere in the United States and will continue to\n\ndo so. The Accused Products, including features of, e.g., the Grace Hopper Superchip (GH200), at least\n\nwhen used for their ordinary and customary purposes, practice each element of at least claim 16 of the\n\n\u2019867 Patent as demonstrated below.\n\n 63. For example, claim 16 of the \u2019867 Patent recites:\n\n 16. A method for performing a numerical simulation on input data\n in a computer system including a central processing unit and an\n accelerator, the method comprising:\n\n receiving, by an accelerator, first input data from the central\n processing unit;\n\n transferring, by an accelerator controller, the first input data into a\n first partition, referenced by first pointer, of an accelerator memory\n before a first computational cycle of the numerical simulation;\n\n performing, by at least one graphics processing unit during the first\n computational cycle, at least one calculation on the first portion of\n the input data as to generate first output data;\n\n\n\n\n 21\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 23 22\n of 95\n of 94\n\n\n\n\n storing, by the accelerator controller, the first output data into a\n second partition, referenced by a second pointer, of the accelerator\n memory; and\n\n swapping the first pointer with the second pointer at the end of the\n first computational cycle, such that the first output data becomes an\n input for a second computational cycle of the numerical simulation.\n\n 64. The Accused Products perform each step of the method of claim 16 of the \u2019867\n\nPatent. To the extent the preamble is construed to be limiting, the Accused Products perform a\n\nmethod for performing a numerical simulation on input data in a computer system including a\n\ncentral processing unit and an accelerator, as further explained below. For instance, the Grace\n\nHopper Superchip (GH200) \u201cbrings together the groundbreaking performance of the NVIDIA\n\nHopper GPU with the versatility of the NVIDIA Grace\u2122 CPU . . . in a single Superchip.\u201d\n\n\n\n\n 22\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 24 23\n of 95\n of 94\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 65. The \u201cGrace Hopper Superchip is the first true heterogeneous accelerated platform\n\nfor high-performance computing (HPC) and AI workloads. It accelerates applications with the\n\nstrengths of both GPUs and CPUs while providing the simplest and most productive heterogeneous\n\nprogramming model to date.\u201d\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 66. In addition, the Accused Products, including the Grace Hopper Superchip,\n\nimplement CUDA, Nvidia\u2019s proprietary \u201cparallel computing platform and programming model.\u201d\n\nCUDA enables NVIDIA GPUs to be used for general purpose computing tasks. CUDA further\n\nincludes the CUDA Toolkit, which \u201cincludes GPU-accelerated libraries, a compiler, development\n\ntools and the CUDA runtime.\u201d As an example, the \u201cCUDA\u00ae Deep Neural Network library\n\n(cuDNN) is a GPU-acceleration library of primitives for deep neural networks.\u201d It \u201cprovides\n\nhighly tuned implementations for standard routines\u201d for GPU-based acceleration.\n\n\n\n\n 23\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 25 24\n of 95\n of 94\n\n\n\n\n(See https://developer.nvidia.com/cuda-zone (emphasis added).)\n\n\n\n\n(See https://developer.nvidia.com/cudnn (emphasis added).)\n\n 67. Nvidia GPU architectures that implement CUDA and cuDNN include the Hopper\n\n(e.g., Grace Hopper Superchip (GH200), H100), Ada Lovelace, Ampere, Turing, Volta, Pascal,\n\nand Maxwell GPU architectures of the Accused Products.\n\n\n\n\n 24\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 26 25\n of 95\n of 94\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-896/support-matrix/index.html\n\n(emphasis added).)\n\n 68. The Accused Products perform a method that includes receiving, by an accelerator,\n\nfirst input data from the central processing unit. For instance, the \u201cCUDA programming model\u201d\n\nimplements programming functions and instructions for CPUs and GPUs. \u201cThe host is the CPU\n\navailable in the system\u201d and \u201csystem memory associated with the CPU is called host memory.\u201d\n\n\u201cThe GPU is called a device and GPU memory likewise called device memory.\u201d As an example,\n\nthe first main CUDA program execution step is \u201c[c]opy[ing] the input data from host [CPU]\n\nmemory to device [GPU] memory, also known as host-to-device transfer.\u201d\n\n\n\n\n 25\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 27 26\n of 95\n of 94\n\n\n\n\n(See https://developer.nvidia.com/blog/cuda-refresher-cuda-programming-model/ (emphasis\n\nadded).)\n\n 69. The Accused Products practice a method that includes transferring, by an\n\naccelerator controller, the first input data into a first partition, referenced by first pointer, of an\n\naccelerator memory before a first computational cycle of the numerical simulation. For instance,\n\nthe GPU architecture of the Accused Products implements a controller. As an example, the\n\nHopper-GPU architecture implements \u201cHBM3 memory controllers\u201d including \u201c12 512-bit\n\nmemory controllers\u201d coupled GPU memory including \u201c6 HBM3 or HBM2e stacks,\u201d \u201c80 GB\n\nHBM3, 5 HBM3 stacks,\u201d and \u201c80 GB HBM2e, 5 HBM2e stacks.\u201d\n\n\n\n\n 26\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 28 27\n of 95\n of 94\n\n\n\n\n(See https://developer.nvidia.com/blog/nvidia-hopper-architecture-in-depth/ (emphasis added).)\n\n 70. The Accused Products implement CUDA, Nvidia\u2019s parallel computing platform.\n\nCUDA enables NVIDIA GPUs to be used for general purpose computing tasks and includes\n\nspecialized GPU-acceleration libraries such as cuDNN. Examples of parameters used in CUDA\n\ninclude pointers \u201cdst\u201d (\u201cDestination memory address\u201d) and \u201csrc\u201d (\u201cSource memory address\u201d). For\n\ninstance, exemplary CUDA function \u201ccudaMemcpy\u201d copies \u201cbytes [data] from the memory area\n\npointed to by src [source memory address pointer] to the memory area pointed to by dst\n\n\n\n 27\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 29 28\n of 95\n of 94\n\n\n\n\n[destination memory address pointer], where kind [type of transfer] specifies the direction of the\n\ncopy.\u201d One of the destinations is \u201ccudaMemcpyHostToDevice,\u201d or host (CPU) to device (GPU).\n\n\n\n\n(See https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__MEMORY.html\n\n(emphasis added).)\n\n 71. The Accused Products practice a method that includes performing, by at least one\n\ngraphics processing unit during the first computational cycle, at least one calculation on the first\n\nportion of the input data as to generate first output data. For instance, CUDA uses \u201cstreams\u201d to\n\nexecute a sequence of commands in order. As shown below, an exemplary CUDA function\n\n\u201ccudaMemcpyAsync\u201d is used to copy data between a host (CPU) and a device (GPU). \u201cEach\n\nstream copies its portion of input array hostPtr [pointer for CPU] to array inputDevPtr in device\n\n[GPU] memory.\u201d The stream then \u201cprocesses inputDevPtr on the device [GPU] by calling\n\nMyKernel(), and copies the result outputDevPtr back to the same portion of hostPtr.\u201d\n\n\n\n\n 28\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 30 29\n of 95\n of 94\n\n\n\n\n(See https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#creation-and-\n\ndestruction-of-streams (emphasis added).)\n\n 72. The Accused Products practice a method that includes storing, by the accelerator\n\ncontroller, the first output data into a second partition, referenced by a second pointer, of the\n\naccelerator memory. For instance, exemplary excerpts of CUDA code shown below demonstrate\n\nCUDA being used to calculate a square sub-matrix Csub of matrix C using the function MatMul.\n\nAn exemplary CUDA stream \u201callocate[s] [matrix] C in device memory.\u201d After Matrices A and B\n\nare synchronized and multiplied, the exemplary CUDA stream \u201c[w]rite[s] Csub to device [GPU]\n\nmemory.\u201d\n\n\n\n\n 29\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 31 30\n of 95\n of 94\n\n\n\n\n *****\n\n\n\n\n(See https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#shared-memory\n\n(emphasis added).)\n\n 73. In addition, exemplary CUDA function \u201ccudaMalloc\u201d is used to \u201callocate weight,\n\nwork, and reserve space buffer sizes in the GPU memory.\u201d \u201cThe work-space buffer is used for\n\ntemporary storage\u201d and the \u201c content can be discarded or modified after all GPU kernels launched\n\nby the corresponding API complete.\u201d The \u201creserve-space buffer\u201d used to transfer intermediate\n\nresults is used for transferring \u201cintermediate results\u201d as used in the cuDNN GPU-acceleration\n\nlibrary for CUDA.\n\n\n 30\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 32 31\n of 95\n of 94\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-\n\n893/api/index.html#cudnnGetMultiHeadAttnBuffers (emphasis added).)\n\n 74. The Accused Products practice a method that includes swapping the first pointer\n\nwith the second pointer at the end of the first computational cycle, such that the first output data\n\nbecomes an input for a second computational cycle of the numerical simulation. For example, the\n\ncuDNN GPU-acceleration library of the Accused Products implement operations that \u201ctake tensors\n\nas input and produce tensors as output.\u201d\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-881/developer-\n\nguide/index.html#tensors-layouts (emphasis added).)\n\n\n\n\n 31\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 33 32\n of 95\n of 94\n\n\n\n\n 75. Nvidia confirms that CUDA implements pointer swapping for device (GPU) pointers.\n\n\n\n\n *****\n\n\n\n\n(See https://forums.developer.nvidia.com/t/swap-device-pointers/38964 (emphasis added).)\n\n\n\n\n 32\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 34 33\n of 95\n of 94\n\n\n\n\n(See https://docs.nvidia.com/cuda/cuda-c-programming-guide/#creation-and-destruction-of-\n\nstreams (emphasis added).)\n\n 76. Each claim in the \u2019867 Patent recites an independent invention. Neither claim 16,\n\ndescribed above, nor any other individual claim is representative of all claims in the \u2019867 Patent.\n\n 77. Defendant has been aware of the technology patented by the \u2019867 Patent since at\n\nleast 2007, when the inventors of the Asserted Patents first discussed their patented technologies\n\n\n\n 33\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 35 34\n of 95\n of 94\n\n\n\n\nwith Mr. Sanford Russell, then the CTO of Nvidia. At the time, the inventors asked Defendant to\n\ncollaborate with them on training neural networks using Nvidia\u2019s GPUs. Defendant informed the\n\ninventors, through Mr. Russell, that it was not interested in the collaboration. Defendant has also\n\ncited the application for the \u2019867 Patent in its own patent portfolio since at least June 28, 2010.\n\n\n\n\n *****\n\n\n\n\n(See https://patents.google.com/patent/US8648867B2/en?oq=8648867#citedBy (emphasis\n\nadded).)\n\n\n\n\n *****\n\n\n\n\n 34\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 36 35\n of 95\n of 94\n\n\n\n\n(See https://patentimages.storage.googleapis.com/ee/13/e9/61df149c3fddc7/US8922566.pdf\n\n(Nvidia U.S. Patent No. 8,922,566) (emphasis added).)\n\n\n\n\n(See\n\nhttps://patentcenter.uspto.gov/applications/13335850/displayReferences/referenceForms?applicat\n\nion= (Nvidia U.S. Appl. No. 13/335,850 August 12, 2014, List of References Cited by Examiner)\n\n(emphasis added).)\n\n 78. Starting in or around 2016, the inventors of the Asserted Patents held multiple\n\ndiscussions with Nvidia to invest in or purchase their AI company, Neurala, Inc., and all its assets,\n\nincluding the \u2019867 Patent and its related patents and applications. These discussions included at\n\nleast Mr. Alvin Lin, an Nvidia Senior Director of Business Development, and Mr. Jeff Herbst, then\n\nan Nvidia Vice President of Business Development and head of Nvidia\u2019s Inception GPU Ventures,\n\nin or around September 6, 2016. In or around October 2016, Nvidia, through its representatives,\n\n\n 35\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 37 36\n of 95\n of 94\n\n\n\n\ninitiated discussions with the inventors to invest in Neurala, Inc. for approximately $10 million.\n\n 79. The inventors also discussed their patented technology, in addition to the \u2019867\n\nPatent and its family, with Defendant\u2019s representatives at Nvidia\u2019s artificial intelligence\n\nconference in or around June 2017. On or about June 26, 2017, Defendant received materials from\n\nthe inventors, in lieu of a meeting on or about June 29, that identified the \u2019867 Patent and its family\n\nand described the technology in detail. Defendant had previously stated it was interested in the\n\ninventors\u2019 solutions. Defendant also featured the inventors on its website as members of\n\nDefendant\u2019s start-up incubator on or about September 25, 2019.\n\n\n\n\n *****\n\n\n\n\n(See https://developer.nvidia.com/blog/inception-spotlight-ai-startup-neurala-sees-7x-speedup-\n\nwith-ngc/ (September 25, 2019); see also https://www.youtube.com/watch?v=-WBtxGLoQNs\n\n(\u201cNeurala Accelerating AI Video Annotation with NGC Containers\u201d posted by Defendant\u2019s\n\nYouTube account).)\n\n 80. Neural AI and/or its predecessors-in-interest have satisfied all statutory obligations\n\nrequired to collect pre-filing damages for the full period allowed by law for infringement of the\n\n\n 36\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 38 37\n of 95\n of 94\n\n\n\n\n\u2019867 Patent.\n\n 81. Defendant directly infringes at least claim 16 of the \u2019867 Patent, either literally or\n\nunder the doctrine of equivalents, by performing the steps described above. For example,\n\nDefendant performs the claimed method in an infringing manner as described above by\n\nimplementing the Accused Products as part of its accelerated computing operations and running\n\ncorresponding software that implements the infringing performance. Defendant also performs the\n\nclaimed method in an infringing manner when testing the operation of the Accused Products and\n\ncorresponding systems. As another example, Defendant performs the claimed method when\n\nproviding or administering services to third parties, customers, and partners using the Accused\n\nProducts.\n\n 82. Defendant\u2019s partners, customers, and users of its Accused Products and\n\ncorresponding systems and services directly infringe at least claim 16 of the \u2019867 Patent, literally\n\nor under the doctrine of equivalents, at least by using the Accused Products and corresponding\n\nsystems and services, as described above.\n\n 83. Defendant has actively induced and is actively inducing infringement of at least\n\nclaim 16 of the \u2019867 Patent with specific intent to induce infringement, and/or willful blindness to\n\nthe possibility that its acts induce infringement, in violation of 35 U.S.C. \u00a7 271(b). For example,\n\nDefendant encourages and induces customers to use Nvidia\u2019s CUDA platform in a manner that\n\ninfringes claim 16 of the \u2019867 Patent at least by offering and providing software that performs a\n\nmethod that infringes claim 16 when installed and operated by the customer using the Accused\n\nProducts, and by engaging in activities relating to selling, marketing, advertising, promotion,\n\ninstallation, support, and distribution of the Accused Products.\n\n 84. Defendant encourages, instructs, directs, and/or requires third parties\u2014including\n\n\n\n\n 37\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 39 38\n of 95\n of 94\n\n\n\n\nits certified partners and/or customers\u2014to perform the claimed method using the software,\n\nplatform, services, and systems in infringing ways, as described above.\n\n 85. Defendant further encourages and induces its customers to infringe claim 16 of the\n\n\u2019867 Patent: 1) by making its accelerated computing and data center services available on its\n\nwebsite, providing applications that allow users to access those services, widely advertising those\n\nservices, and providing technical support and instructions to users (see\n\nhttps://www.nvidia.com/en-us/data-center/data-center-gpus/gpu-test-drive/); and 2) through\n\nactivities relating to marketing, advertising, promotion, installation, support, and distribution of\n\nthe Accused Products, including its CUDA platform, and services in the United States. (See\n\nhttps://www.nvidia.com/en-us/; see https://www.nvidia.com/en-us/about-nvidia/partners/;\n\nhttps://www.nvidia.com/en-us/data-center/where-to-buy/; https://www.nvidia.com/en-us/data-\n\ncenter/where-to-buy-tesla/.)\n\n 86. For example, Defendant shares instructions, guides, and manuals, which advertise\n\nand instruct third parties on how to use its hardware and platform as described above, including at\n\nleast customers and partners. (See https://docs.nvidia.com/cuda/cuda-c-programming-guide/.)\n\nDefendant also provides customer service and technical support to purchasers of the Accused\n\nProducts and corresponding systems and services, which directs and encourages customers to\n\nperform certain actions that use the Accused Products in an infringing manner. (See\n\nhttps://www.nvidia.com/en-us/support/; https://www.nvidia.com/en-\n\nus/support/enterprise/services/.)\n\n 87. Defendant and/or Defendant\u2019s partners recommend and sell the Accused Products\n\nand provide technical support for the installation, implementation, integration, and ongoing\n\noperation of the Accused Products for each individual customer. On information and belief, each\n\n\n\n\n 38\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 40 39\n of 95\n of 94\n\n\n\n\ncustomer enters into a contractual relationship with Defendant and/or one of Defendant\u2019s partners,\n\nwhich obligates each customer to perform certain actions in order to use the Accused Products.\n\n(See https://www.nvidia.com/en-us/agreements/; https://www.nvidia.com/en-\n\nus/agreements/cloud-services/nvidia-cloud-agreement/; https://www.nvidia.com/en-\n\nus/agreements/cloud-services/service-specific-terms-for-nvidia-dgx-cloud/.) Further, in order to\n\nreceive the benefit of Defendant\u2019s and/or its partner\u2019s continued technical support and their\n\nspecialized knowledge and guidance of the operability of the Accused Products, each customer\n\nmust continue to use the Accused Products in a way that infringes the \u2019867 Patent. (See\n\nhttps://www.nvidia.com/en-us/support/.)\n\n 88. Further, as the entity that provides installation, implementation, and integration of\n\nthe Accused Products in addition to ensuring the Accused Product remains operational for each\n\ncustomer through ongoing technical support, on information and belief, Defendant and/or\n\nDefendant\u2019s partners affirmatively aid and abet each customer\u2019s use of the Accused Products in a\n\nmanner that performs the claimed method of, and infringes, the \u2019867 Patent.\n\n 89. Defendant also contributes to the infringement of its partners, customers, and users\n\nof the Accused Products by providing within the United States or importing into the United States\n\nthe Accused Products, which are for use in practicing, and under normal operation practice, the\n\nmethods, systems, and devices claimed in the Asserted Patents, constituting a material part of the\n\ninventions claimed, and not a staple article or commodity of commerce suitable for substantial\n\nnon-infringing uses. Indeed, as shown above, the Accused Products and the example functionality\n\nhave no substantial non-infringing uses but are specifically designed to practice the \u2019867 Patent.\n\n 90. On information and belief, the infringing actions of each partner, customer, and/or\n\nuser of the Accused Products are attributable to Defendant. For example, on information and belief,\n\n\n\n\n 39\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 41 40\n of 95\n of 94\n\n\n\n\nDefendant directs and controls the activities or actions of its partners or others in connection with\n\nthe Accused Products by contractual agreement or otherwise requiring partners or others to provide\n\ninformation and instructions to customers who acquire the Accused Products which, when\n\nfollowed, results in infringement. Defendant further directs and controls the operation of devices\n\nexecuting the Accused Products by programming the software which, when executed by a\n\ncustomer or user, performs the claimed method of at least claim 16 of the \u2019867 Patent.\n\n 91. Plaintiff has suffered and continue to suffer damages as a result of Defendant\u2019s\n\ninfringement of the \u2019867 Patent. Defendant is therefore liable to Plaintiff under 35 U.S.C. \u00a7 284\n\nfor damages in an amount that adequately compensates Plaintiff for Defendant\u2019s infringement, but\n\nno less than a reasonable royalty.\n\n 92. Defendant\u2019s infringement of the \u2019867 Patent is knowing and willful. Defendant had\n\nactual knowledge of the \u2019867 Patent application since at least 2010 and actual knowledge of the\n\n\u2019867 Patent, and its family, since at least 2017.\n\n 93. On information and belief, despite Defendant\u2019s knowledge of the Asserted Patents\n\nand Plaintiff\u2019s patented technology, Defendant made the deliberate decision to sell products and\n\nservices that it knew infringe these patents. Defendant\u2019s continued infringement of the \u2019867 Patent\n\nwith knowledge of the \u2019867 Patent constitutes willful infringement.\n\n SECOND CAUSE OF ACTION\n (INFRINGEMENT OF THE \u2019438 PATENT)\n\n 94. Plaintiff realleges and incorporates by reference the allegations of the preceding\n\nparagraphs of this Complaint.\n\n 95. Defendant has infringed and continues to infringe one or more claims of the \u2019438 Patent\n\nin violation of 35 U.S.C. \u00a7 271 in this District and elsewhere in the United States and will continue to\n\ndo so. The Accused Products, including features of, e.g., the Grace Hopper Superchip (GH200), at least\n\n\n\n 40\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 42 41\n of 95\n of 94\n\n\n\n\nwhen used for their ordinary and customary purposes, practice each element of at least claim 21 of the\n\n\u2019438 Patent as demonstrated below.\n\n 96. For example, claim 21 of the \u2019438 Patent recites:\n\n 21. A method of performing a sequence of computations\n representing an artificial neural network, the method comprising:\n\n receiving, at a central processing unit (CPU), first input data\n acquired from an external system in real time;\n\n initializing, by a controller operably coupled to a graphics\n processing unit (GPU), textures and shaders in a memory operably\n coupled to the GPU;\n\n transferring the first input data received by the CPU to the memory\n operably coupled to the GPU;\n\n performing, by the graphics processing unit (GPU), a first\n computation in the sequence of computations on the first input data\n based on the textures and shaders to generate first output data,\n computations in the sequence of computations representing\n respective layers of neurons in the artificial neural network, an\n output of the first computation in the sequence of computations\n representing an output of a first neuron in a first layer in the artificial\n neural network;\n\n storing, in the memory operably coupled to the GPU, the first input\n data and the first output data; and\n\n transferring second input data acquired from the external system in\n real time into the memory operably coupled to the GPU after the\n GPU starts the first computation and before the GPU starts a second\n computation of the sequence of computations, an output of the\n second computation in the sequence of computations representing\n an output of a second neuron in a second layer in the artificial neural\n network.\n\n 97. The Accused Products perform each step of the method of claim 21 of the \u2019438\n\nPatent. To the extent the preamble is construed to be limiting, the Accused Products perform a\n\nmethod of performing a sequence of computations representing an artificial neural network, as\n\nfurther explained below. For instance, the Grace Hopper Superchip (GH200) \u201cbrings together the\n\n\n\n 41\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 43 42\n of 95\n of 94\n\n\n\n\ngroundbreaking performance of the NVIDIA Hopper GPU with the versatility of the NVIDIA\n\nGrace\u2122 CPU . . . in a single Superchip.\u201d It includes the cuDNN (CUDA Deep Neural Network)\n\nlibrary for \u201c[d]eep neural networks.\u201d\n\n\n\n\n *****\n\n\n\n\n 42\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 44 43\n of 95\n of 94\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 98. The \u201cGrace Hopper Superchip is the first true heterogeneous accelerated platform\n\nfor high-performance computing (HPC) and AI workloads. It accelerates applications with the\n\nstrengths of both GPUs and CPUs while providing the simplest and most productive heterogeneous\n\nprogramming model to date.\u201d\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 99. In addition, the Accused Products, including the Grace Hopper Superchip,\n\nimplement CUDA, Nvidia\u2019s proprietary \u201cparallel computing platform and programming model.\u201d\n\nCUDA further includes the CUDA Toolkit, which \u201cincludes GPU-accelerated libraries, a\n\ncompiler, development tools and the CUDA runtime.\u201d As an example, the \u201cCUDA\u00ae Deep Neural\n\nNetwork library (cuDNN) is a GPU-acceleration library of primitives for deep neural networks.\u201d\n\n\n\n 43\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 45 44\n of 95\n of 94\n\n\n\n\nIt \u201cprovides highly tuned implementations for standard routines\u201d for GPU-based acceleration.\n\n\n\n\n(See https://developer.nvidia.com/cuda-zone (emphasis added).)\n\n\n\n\n(See https://developer.nvidia.com/cudnn (emphasis added).)\n\n 100. Nvidia GPU architectures that implement CUDA and cuDNN include the Hopper\n\n(e.g., Grace Hopper Superchip (GH200), H100), Ada Lovelace, Ampere, Turing, Volta, Pascal,\n\nand Maxwell GPU architectures of the Accused Products.\n\n\n\n\n 44\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 46 45\n of 95\n of 94\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-896/support-matrix/index.html\n\n(emphasis added).)\n\n 101. The Accused Products perform a method that includes receiving, at a central\n\nprocessing unit (CPU), first input data acquired from an external system in real time. For instance,\n\nas illustrated below, a diagram describing the architecture of the Grace Hopper Superchip depicts\n\na CPU (\u201cGrace CPU\u201d) with \u201c[u]p to 72 cores\u201d that receives and sends input and output data via\n\n\u201cHigh-Speed IO\u201d (\u201cPCIe-5\u201d). The Grace CPU is further depicted as being coupled to memory\n\n\u201cCPU LPDDR5X\u201d up to 480GB via a link up to \u201c500 GB/s.\u201d\n\n\n\n\n 45\n\fCase\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 47 46\n of 95\n of 94\n\n\n\n\n *****\n\n\n\n\n 46\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 48 47\n of 95\n of 94\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 102. In a related diagram example, \u201cCPU PHYSICAL MEMORY\u201d (LPDDR5X) is\n\nillustrated as being accessed by a CPU (\u201cCPU-resident access\u201d).\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 103. As previously stated, the Accused Products implement CUDA and specialized\n\nGPU-acceleration libraries such as cuDNN. \u201cCUDA\u00ae is a parallel computing platform and\n\n\n\n 47\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 49 48\n of 95\n of 94\n\n\n\n\nprogramming model developed by NVIDIA for general computing on graphical processing units\n\n(GPUs)\u201d including \u201cGPU-accelerated applications.\u201d In GPU-accelerated applications, \u201cthe\n\nsequential part of the workload runs on the CPU \u2013 which is optimized for single-threaded\n\nperformance \u2013 while the compute intensive portion of the application runs on thousands of GPU\n\ncores in parallel.\u201d\n\n\n\n\n(See https://developer.nvidia. com/cuda-zone (emphasis added).)\n\n 104. The \u201cCUDA programming model\u201d implements programming functions and\n\ninstructions for CPUs and GPUs. \u201cThe host is the CPU available in the system\u201d and \u201csystem\n\nmemory associated with the CPU is called host memory.\u201d As an example, the first main CUDA\n\nprogram execution step is \u201c[c]opy[ing] the input data from host [CPU] memory.\u201d\n\n\n\n\n 48\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 50 49\n of 95\n of 94\n\n\n\n\n(See https://developer.nvidia.com/blog/cuda-refresher-cuda-programming-model/ (emphasis\n\nadded).)\n\n 105. The Accused Products perform a method that includes initializing, by a controller\n\noperably coupled to a graphics processing unit (GPU), textures and shaders in a memory operably\n\ncoupled to the GPU. For instance, as illustrated below, a GPU (\u201cHopper GPU\u201d) for the Grace\n\nHopper Superchip is depicted as accessing both CPU and GPU memory using \u201cNVLINK\u201d for both\n\naccessing and storing data. Indeed, \u201cNVIDIA GH200 is designed to accelerate applications with\n\nexceptionally large memory footprints.\u201d As illustrated, the Hopper GPUs are illustrated coupled\n\nto \u201cGPU HBM3\u201d high bandwidth memory or \u201cGPU HBM3e\u201d high bandwidth memory.\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 106. The GPU architecture of the Accused Products implements a controller. As an\n\nexample, the Hopper-GPU architecture includes \u201cGPU processing clusters\u201d and \u201ctexture\n\nprocessing clusters\u201d and implements \u201cHBM3 memory controllers\u201d including \u201c12 512-bit memory\n\ncontrollers\u201d coupled GPU memory including \u201c6 HBM3 or HBM2e stacks,\u201d \u201c80 GB HBM3, 5\n\nHBM3 stacks,\u201d and \u201c80 GB HBM2e, 5 HBM2e stacks.\u201d\n\n\n\n\n 49\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 51 50\n of 95\n of 94\n\n\n\n\n(See https://developer.nvidia.com/blog/nvidia-hopper-architecture-in-depth/ (emphasis added).)\n\n 107. In addition, CUDA includes the exemplary NPP (Nvidia Performance Primitives)\n\nlibrary \u201cfor performing CUDA accelerated processing\u201d and \u201cperforming CUDA accelerated\n\nprocessing for 2D image and signal processing.\u201d\n\n\n\n\n 50\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 52 51\n of 95\n of 94\n\n\n\n\n *****\n\n\n\n\n(See https://docs.nvidia.com/cuda/index.html (emphasis added).)\n\n\n\n\n(See https://docs.nvidia.com/cuda/npp/introduction.html (emphasis added).)\n\n 108. As an example, the exemplary CUDA NPP library passes image data using \u201c[a]\n\npointer to the image\u2019s underlying data type\u201d and \u201c[a] line step in bytes.\u201d In this example, the\n\npointer is passed \u201cto the underlying pixel data type\u201d and the pointer and line step are passed\n\nindividually for processing involving \u201cimage data.\u201d\n\n\n\n\n 51\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 53 52\n of 95\n of 94\n\n\n\n\n(See\n\nhttps://docs.nvidia.com/cuda/npp/introduction.html#nppi_conventions_lb_1passing_image_data\n\n(emphasis added).)\n\n 109. As another example, the exemplary CUDA NPP library implements function for\n\nimage color conversion. These functions \u201cmanipulat[e] an image\u2019s color model and sampling\n\nformat\u201d and \u201ccan be found in the nppicc [NVIDIA Performance Primitives Image Color\n\nConversion] library.\u201d As shown, these functions save \u201capplication load time\u201d and \u201cCUDA\n\nruntime.\u201d\n\n\n\n\n(See https://docs.nvidia.com/cuda/npp/image_color_conversion.html#image-color-model-\n\nconversion-functions (emphasis added).)\n\n 110. The Accused Products perform a method that includes transferring the first input\n\n\n 52\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 54 53\n of 95\n of 94\n\n\n\n\ndata received by the CPU to the memory operably coupled to the GPU. For instance, the \u201cCUDA\n\nprogramming model\u201d implements programming functions and instructions for CPUs and GPUs.\n\n\u201cThe host is the CPU available in the system\u201d and \u201csystem memory associated with the CPU is\n\ncalled host memory.\u201d \u201cThe GPU is called a device and GPU memory likewise called device\n\nmemory.\u201d As an example, the first main CUDA program execution step is \u201c[c]opy[ing] the input\n\ndata from host [CPU] memory to device [GPU] memory, also known as host-to-device transfer.\u201d\n\n\n\n\n(See https://developer.nvidia.com/blog/cuda-refresher-cuda-programming-model/ (emphasis\n\nadded).)\n\n 111. The Accused Products perform a method that includes performing, by the graphics\n\nprocessing unit (GPU), a first computation in the sequence of computations on the first input data\n\nbased on the textures and shaders to generate first output data, computations in the sequence of\n\ncomputations representing respective layers of neurons in the artificial neural network, an output\n\nof the first computation in the sequence of computations representing an output of a first neuron\n\nin a first layer in the artificial neural network. For instance, the CUDA platform programming\n\nimplemented in the Accused Products utilizes the GPU and GPU memory. As an example, after\n\nthe \u201chost-to-device transfer\u201d (host (CPU) memory to device (GPU) memory), the second main\n\n\n 53\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 55 54\n of 95\n of 94\n\n\n\n\nstep is \u201c[l]oad the GPU program and execute, caching data on-chip for performance.\u201d\n\n\n\n\n(See https://developer.nvidia.com/blog/cuda-refresher-cuda-programming-model/ (emphasis\n\nadded).)\n\n 112. In addition, as previously stated, cuDNN is a CUDA \u201cGPU-acceleration library of\n\nprimitives for deep neural networks.\u201d (See https://developer.nvidia.com/cudnn.) The exemplary\n\ncuDNN release notes below demonstrate computations implemented for RNNs and related data\n\nbeing transferred to GPU memory. As shown, users do \u201cnot need to transfer [an] array [from RNN\n\ndata descriptors] to device memory; the operation will be performed automatically by RNN APIs.\u201d\n\n\n\n\n *****\n\n\n\n\n 54\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 56 55\n of 95\n of 94\n\n\n\n\n *****\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-893/release-\n\nnotes/index.html#abstract (emphasis added).)\n\n 113. Relatedly, cuDNN operations below exemplify tensors being used as inputs and\n\noutputs (e.g., Tmp0). Exemplary \u201ccuDNN operations take tensors as input and produce tensors as\n\noutput.\u201d As part of CUDA, these cuDNN operations implement computer tasks performed by a\n\nGPU.\n\n\n\n\n 55\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 57 56\n of 95\n of 94\n\n\n\n\n *****\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-881/developer-\n\nguide/index.html#tensors-layouts (emphasis added).)\n\n 114. The Accused Products perform a method that includes storing, in the memory\n\noperably coupled to the GPU, the first input data and the first output data. For instance, as\n\nillustrated below, a diagram describing the architecture of the Grace Hopper Superchip depicts a\n\nGPU (\u201cHopper GPU\u201d) in communication with GPU memory (\u201cGPUHBM3 or HBm3e\u201d high\n\nbandwidth memory).\n\n\n\n\n 56\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 58 57\n of 95\n of 94\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 115. As previously stated, the \u201cCUDA programming model\u201d implements programming\n\nfunctions and instructions for CPUs (host) and GPUs (device). For example, after the \u201chost-to-\n\ndevice transfer\u201d (CPU to GPU) first main step and \u201c[l]oad[ing] the GPU program and execut[ing]\u201d\n\n\n 57\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 59 58\n of 95\n of 94\n\n\n\n\nand \u201ccaching data on-chip for performance\u201d for the second main step, the \u201cresults\u201d are stored on\n\nGPU \u201cdevice memory.\u201d\n\n\n\n\n(See https://developer.nvidia.com/blog/cuda-refresher-cuda-programming-model/ (emphasis\n\nadded.)\n\n 116. The Accused Products perform a method that includes transferring second input\n\ndata acquired from the external system in real time into the memory operably coupled to the GPU\n\nafter the GPU starts the first computation and before the GPU starts a second computation of the\n\nsequence of computations, an output of the second computation in the sequence of computations\n\nrepresenting an output of a second neuron in a second layer in the artificial neural network. For\n\ninstance, as illustrated below, a diagram describing the architecture of the Grace Hopper Superchip\n\ndepicts a CPU (\u201cGrace CPU\u201d) in communication with a GPU (\u201cHopper GPU\u201d) via \u201cNVLink-C2C\u201d\n\n(chip-to-chip). \u201cHigh-Speed IO\u201d input and output data is received by the CPU via \u201cPCIe-5.\u201d\n\n\n\n\n 58\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 60 59\n of 95\n of 94\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 117. Furthermore, the Accused Products, including the Grace Hopper Superchip,\n\nimplement libraries and SDKs designed for neural networks that \u201care created from large numbers\n\nof identical neurons [that] are highly parallel by nature.\u201d The Accused Products implement\n\n\n 59\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 61 60\n of 95\n of 94\n\n\n\n\ncuDNN, a library \u201cmakes it easy to obtain state-of-the-art performance with Deep Neural\n\nNetworks,\u201d and TensorRT, a platform accelerator and runtime for optimizing, validating, and\n\ndeploying neural networks for inference (e.g., applying knowledge from a trained neural network\n\nmodel and inferring a result).\n\n\n\n\n(See https://developer.nvidia.com/discover/artificial-neural-network (emphasis added).)\n\n 118. An example below illustrates an exemplary neural network the Accused Products\n\nare designed to accelerate using parallel computations. \u201cInput\u201d (four) and \u201cOutput\u201d (eight) neurons\n\nare depicted below in a full-connected or linear layer structure in which all of the input neurons\n\ndepicted in a first layer are connected to all of the output neurons depicted in a second layer.\n\nComputations for the neural network are performed using, for example, \u201cNVIDIA Matrix\n\nMultiplication.\u201d Examples of inputs and outputs for forward propagation, activation gradient\n\ncomputation, and weight gradient computation (as matrix by matrix multiplications) are shown\n\nbelow.\n\n\n\n\n 60\n\fCase\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 62 61\n of 95\n of 94\n\n\n\n\n 61\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 63 62\n of 95\n of 94\n\n\n\n\n *****\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/performance/dl-performance-fully-\n\nconnected/index.html#performance (annotations added).)\n\n\n 62\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 64 63\n of 95\n of 94\n\n\n\n\n 119. Indeed, the cuDNN GPU-acceleration library of the Accused Products implement\n\noperations that \u201ctake tensors as input and produce tensors as output.\u201d\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-881/developer-\n\nguide/index.html#tensors-layouts (emphasis added).)\n\n 120. Each claim in the \u2019438 Patent recites an independent invention. Neither claim 21,\n\ndescribed above, nor any other individual claim is representative of all claims in the \u2019438 Patent.\n\n 121. Defendant has been aware of the \u2019438 Patent since at least the filing of the original\n\nComplaint. Defendant has been aware of the technology patented by the \u2019438 Patent since at least\n\n2007, when the inventors of the Asserted Patents first discussed their patented technologies with\n\nMr. Sanford Russell, then the CTO of Nvidia. At the time, the inventors asked Defendant to\n\ncollaborate with them on training neural networks using Nvidia\u2019s GPUs. Defendant informed the\n\ninventors, through Mr. Russell, that it was not interested in the collaboration. Defendant has also\n\ncited an ancestor of the \u2019438 Patent in its own patent portfolio since at least June 28, 2010 (See\n\nhttps://patents.google.com/patent/US8648867B2/en?oq=8648867#citedBy;\n\nhttps://patentimages.storage.googleapis.com/ee/13/e9/61df149c3fddc7/US8922566.pdf;\n\nhttps://patentcenter.uspto.gov/applications/13335850/displayReferences/referenceForms?applicat\n\nion= (Nvidia U.S. Appl. No. 13/335,850 August 12, 2014, List of References Cited by Examiner).)\n\n 122. Starting in or around 2016, the inventors of the Asserted Patents held multiple\n\ndiscussions with Nvidia to invest in or purchase their AI company, Neurala, Inc., and all its assets,\n\nincluding the \u2019438 Patent family. These discussions included at least Mr. Alvin Lin, an Nvidia\n\nSenior Director of Business Development, and Mr. Jeff Herbst, then an Nvidia Vice President of\n\nBusiness Development and head of Nvidia\u2019s Inception GPU Ventures, in or around September 6,\n\n\n 63\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 65 64\n of 95\n of 94\n\n\n\n\n2016. In or around October 2016, Nvidia, through its representatives, initiated discussions with\n\nthe inventors to invest in Neurala, Inc. for approximately $10 million.\n\n 123. The inventors also discussed their patented technology, including the underlying\n\ntechnology and family to the \u2019438 Patent (including U.S. Patent No. 9,189,828, the patent the \u2019438\n\nPatent reissued from), with Defendant\u2019s representatives at Nvidia\u2019s artificial intelligence\n\nconference in or around June 2017. On or about June 26, 2017, Defendant received materials from\n\nthe inventors, in lieu of a meeting on or about June 29, that identified patents related to the \u2019438\n\nPatent and described the technology in detail. Defendant had previously stated it was interested in\n\nthe inventors\u2019 solutions. Defendant also featured the inventors on its website as members of\n\nDefendant\u2019s start-up incubator on or about September 25, 2019.\n\n\n\n\n *****\n\n\n\n\n(See https://developer.nvidia.com/blog/inception-spotlight-ai-startup-neurala-sees-7x-speedup-\n\nwith-ngc/ (September 25, 2019); see also https://www.youtube.com/watch?v=-WBtxGLoQNs\n\n(\u201cNeurala Accelerating AI Video Annotation with NGC Containers\u201d posted by Defendant\u2019s\n\nYouTube account).)\n\n\n 64\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 66 65\n of 95\n of 94\n\n\n\n\n 124. Neural AI and/or its predecessors-in-interest have satisfied all statutory obligations\n\nrequired to collect pre-filing damages for the full period allowed by law for infringement of the\n\n\u2019438 Patent.\n\n 125. Defendant directly infringes at least claim 21 of the \u2019438 Patent, either literally or\n\nunder the doctrine of equivalents, by performing the steps described above. For example,\n\nDefendant performs the claimed method in an infringing manner as described above by\n\nimplementing the Accused Products as part of its accelerated computing operations and running\n\ncorresponding software that implements the infringing performance. Defendant also performs the\n\nclaimed method in an infringing manner when testing the operation of the Accused Products and\n\ncorresponding systems. As another example, Defendant performs the claimed method when\n\nproviding or administering services to third parties, customers, and partners using the Accused\n\nProducts.\n\n 126. Defendant\u2019s partners, customers, and users of its Accused Products and\n\ncorresponding systems and services directly infringe at least claim 21 of the \u2019438 Patent, literally\n\nor under the doctrine of equivalents, at least by using the Accused Products and corresponding\n\nsystems and services, as described above.\n\n 127. Defendant has actively induced and is actively inducing infringement of at least\n\nclaim 21 of the \u2019438 Patent with specific intent to induce infringement, and/or willful blindness to\n\nthe possibility that its acts induce infringement, in violation of 35 U.S.C. \u00a7 271(b). For example,\n\nDefendant encourages and induces customers to use Nvidia\u2019s CUDA platform in a manner that\n\ninfringes claim 21 of the \u2019438 Patent at least by offering and providing software that performs a\n\nmethod that infringes claim 21 when installed and operated by the customer using the Accused\n\nProducts, and by engaging in activities relating to selling, marketing, advertising, promotion,\n\n\n\n\n 65\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 67 66\n of 95\n of 94\n\n\n\n\ninstallation, support, and distribution of the Accused Products.\n\n 128. Defendant encourages, instructs, directs, and/or requires third parties\u2014including\n\nits certified partners and/or customers\u2014to perform the claimed method using the software,\n\nplatform, services, and systems in infringing ways, as described above.\n\n 129. Defendant further encourages and induces its customers to infringe claim 21 of the\n\n\u2019438 Patent: 1) by making its accelerated computing and data center services available on its\n\nwebsite, providing applications that allow users to access those services, widely advertising those\n\nservices, and providing technical support and instructions to users (see\n\nhttps://www.nvidia.com/en-us/data-center/data-center-gpus/gpu-test-drive/); and 2) through\n\nactivities relating to marketing, advertising, promotion, installation, support, and distribution of\n\nthe Accused Products, including its CUDA platform, and services in the United States. (See\n\nhttps://www.nvidia.com/en-us/; see https://www.nvidia.com/en-us/about-nvidia/partners/;\n\nhttps://www.nvidia.com/en-us/data-center/where-to-buy/; https://www.nvidia.com/en-us/data-\n\ncenter/where-to-buy-tesla/.)\n\n 130. For example, Defendant shares instructions, guides, and manuals, which advertise\n\nand instruct third parties on how to use its hardware and platform as described above, including at\n\nleast customers and partners. (See https://docs.nvidia.com/cuda/cuda-c-programming-guide/.)\n\nDefendant also provides customer service and technical support to purchasers of the Accused\n\nProducts and corresponding systems and services, which directs and encourages customers to\n\nperform certain actions that use the Accused Products in an infringing manner. (See\n\nhttps://www.nvidia.com/en-us/support/; https://www.nvidia.com/en-\n\nus/support/enterprise/services/.)\n\n 131. Defendant and/or Defendant\u2019s partners recommend and sell the Accused Products\n\n\n\n\n 66\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 68 67\n of 95\n of 94\n\n\n\n\nand provide technical support for the installation, implementation, integration, and ongoing\n\noperation of the Accused Products for each individual customer. On information and belief, each\n\ncustomer enters into a contractual relationship with Defendant and/or one of Defendant\u2019s partners,\n\nwhich obligates each customer to perform certain actions in order to use the Accused Products.\n\n(See https://www.nvidia.com/en-us/agreements/; https://www.nvidia.com/en-\n\nus/agreements/cloud-services/nvidia-cloud-agreement/; https://www.nvidia.com/en-\n\nus/agreements/cloud-services/service-specific-terms-for-nvidia-dgx-cloud/.) Further, in order to\n\nreceive the benefit of Defendant\u2019s and/or its partner\u2019s continued technical support and their\n\nspecialized knowledge and guidance of the operability of the Accused Products, each customer\n\nmust continue to use the Accused Products in a way that infringes the \u2019438 Patent. (See\n\nhttps://www.nvidia.com/en-us/support/.)\n\n 132. Further, as the entity that provides installation, implementation, and integration of\n\nthe Accused Products in addition to ensuring the Accused Product remains operational for each\n\ncustomer through ongoing technical support, on information and belief, Defendant and/or\n\nDefendant\u2019s partners affirmatively aid and abet each customer\u2019s use of the Accused Products in a\n\nmanner that performs the claimed method of, and infringes, the \u2019438 Patent.\n\n 133. Defendant also contributes to the infringement of its partners, customers, and users\n\nof the Accused Products by providing within the United States or importing into the United States\n\nthe Accused Products, which are for use in practicing, and under normal operation practice, the\n\nmethods, systems, and devices claimed in the Asserted Patents, constituting a material part of the\n\ninventions claimed, and not a staple article or commodity of commerce suitable for substantial\n\nnon-infringing uses. Indeed, as shown above, the Accused Products and the example functionality\n\nhave no substantial non-infringing uses but are specifically designed to practice the \u2019438 Patent.\n\n\n\n\n 67\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 69 68\n of 95\n of 94\n\n\n\n\n 134. On information and belief, the infringing actions of each partner, customer, and/or\n\nuser of the Accused Products are attributable to Defendant. For example, on information and belief,\n\nDefendant directs and controls the activities or actions of its partners or others in connection with\n\nthe Accused Products by contractual agreement or otherwise requiring partners or others to provide\n\ninformation and instructions to customers who acquire the Accused Products which, when\n\nfollowed, results in infringement. Defendant further directs and controls the operation of devices\n\nexecuting the Accused Products by programming the software which, when executed by a\n\ncustomer or user, performs the claimed method of at least claim 21 of the \u2019438 Patent.\n\n 135. Plaintiff has suffered and continues to suffer damages as a result of Defendant\u2019s\n\ninfringement of the \u2019438 Patent. Defendant is therefore liable to Plaintiff under 35 U.S.C. \u00a7 284\n\nfor damages in an amount that adequately compensates Plaintiff for Defendant\u2019s infringement, but\n\nno less than a reasonable royalty.\n\n 136. Defendant\u2019s infringement of the \u2019438 Patent is knowing and willful. Defendant\n\nacquired actual knowledge of the patent that the \u2019438 Patent reissued from, and its family, since at\n\nleast 2017 and has acquired additional knowledge of the \u2019438 Patent since at least the filing of this\n\nlawsuit.\n\n 137. On information and belief, despite Defendant\u2019s knowledge of the Asserted Patents and\n\nPlaintiff\u2019s patented technology, Defendant made the deliberate decision to sell products and services\n\nthat it knew infringe these patents. Defendant\u2019s continued infringement of the \u2019438 Patent with\n\nknowledge of the \u2019438 Patent constitutes willful infringement.\n\n THIRD CAUSE OF ACTION\n (INFRINGEMENT OF THE \u2019461 PATENT)\n\n 138. Plaintiff realleges and incorporates by reference the allegations of the preceding\n\nparagraphs of this Complaint.\n\n\n\n 68\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 70 69\n of 95\n of 94\n\n\n\n\n 139. Defendant has infringed and continues to infringe one or more claims of the \u2019461\n\nPatent in violation of 35 U.S.C. \u00a7 271 in this District and elsewhere in the United States and will\n\ncontinue to do so. The Accused Products, including features of, e.g., the Grace Hopper Superchip\n\n(GH200), at least when used for their ordinary and customary purposes, practice each element of\n\nat least claim 21 of the \u2019461 Patent as demonstrated below.\n\n 140. For example, claim 21 of the \u2019461 Patent recites:\n\n 21. A method of executing computations representing an artificial\n neural network on a computer system comprising at least one central\n processing unit (CPU), a processing unit, a first memory partition,\n and a second memory partition, the method comprising:\n\n executing, by the at least one CPU, a user interaction stream, the\n user interaction stream controlling transfer of inputs to the artificial\n neural network to the first memory partition and the second memory\n partition;\n\n executing, by the processing unit, a computational stream, the\n computational stream controlling data exchange between the user\n interaction stream and the computational stream during execution of\n the computations representing the artificial neural network;\n\n shifting control of a data exchange between the user interaction\n stream and the computational stream to the computational stream in\n response to starting execution of the computations representing the\n artificial neural network;\n\n shifting control of the data exchange between the user interaction\n stream and the computational stream to the user interaction stream\n in response to completion or interruption of the computations\n representing the artificial neural network;\n\n queueing a user command received by the user interaction stream\n during execution of the computations representing the artificial\n neural network; and\n\n executing the user command during execution of the computations\n representing the artificial neural network at times determined by the\n computational stream.\n\n 141. The Accused Products perform each step of the method of claim 21 of the \u2019461\n\n\n\n 69\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 71 70\n of 95\n of 94\n\n\n\n\nPatent. To the extent the preamble is construed to be limiting, the Accused Products perform a\n\nmethod of executing computations representing an artificial neural network on a computer system\n\ncomprising at least one central processing unit (CPU), a processing unit, a first memory partition,\n\nand a second memory partition, as further explained below. For instance, the Grace Hopper\n\nSuperchip (GH200) \u201cbrings together the groundbreaking performance of the NVIDIA Hopper\n\nGPU with the versatility of the NVIDIA Grace\u2122 CPU . . . in a single Superchip.\u201d It includes the\n\ncuDNN (CUDA Deep Neural Network) library for \u201c[d]eep neural networks.\u201d\n\n\n\n\n *****\n\n\n\n\n 70\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 72 71\n of 95\n of 94\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 142. As illustrated below, a diagram describing the architecture of the Grace Hopper\n\nSuperchip depicts a CPU (\u201cGrace CPU\u201d) with \u201c[u]p to 72 cores\u201d and CPU memory (\u201cCPU\n\nLPDDR5X\u201d) and a GPU (\u201cHopper GPU\u201d) and GPU memory (\u201cGPUHBM3 or HBm3e\u201d).\n\n\n\n\n 71\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 73 72\n of 95\n of 94\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 143. The \u201cGrace Hopper Superchip is the first true heterogeneous accelerated platform\n\nfor high-performance computing (HPC) and AI workloads. It accelerates applications with the\n\nstrengths of both GPUs and CPUs while providing the simplest and most productive heterogeneous\n\nprogramming model to date.\u201d\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 144. In addition, the Accused Products, including the Grace Hopper Superchip,\n\nimplement CUDA, Nvidia\u2019s proprietary \u201cparallel computing platform and programming model.\u201d\n\nCUDA further includes the CUDA Toolkit, which \u201cincludes GPU-accelerated libraries, a\n\ncompiler, development tools and the CUDA runtime.\u201d As an example, the \u201cCUDA\u00ae Deep Neural\n\n\n\n 72\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 74 73\n of 95\n of 94\n\n\n\n\nNetwork library (cuDNN) is a GPU-acceleration library of primitives for deep neural networks.\u201d\n\nIt \u201cprovides highly tuned implementations for standard routines\u201d for GPU-based acceleration.\n\n\n\n\n(See https://developer.nvidia.com/cuda-zone (emphasis added).)\n\n\n\n\n(See https://developer.nvidia.com/cudnn (emphasis added).)\n\n 145. Nvidia GPU architectures that implement CUDA and cuDNN include the Hopper\n\n(e.g., Grace Hopper Superchip (GH200), H100), Ada Lovelace, Ampere, Turing, Volta, Pascal,\n\nand Maxwell GPU architectures of the Accused Products.\n\n\n\n\n 73\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 75 74\n of 95\n of 94\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-896/support-matrix/index.html\n\n(emphasis added).)\n\n 146. The Accused Products perform a method that includes executing, by the at least\n\none CPU, a user interaction stream, the user interaction stream controlling transfer of inputs to\n\nthe artificial neural network to the first memory partition and the second memory partition. For\n\ninstance, as shown in the Grace Hopper Superchip architecture diagram below, the Grace Hopper\n\nSuperchip is illustrated below with a CPU (\u201cGRACE CPU\u201d). The CPU \u201cshare[s] a single per-\n\nprocess page table\u201d with a GPU (\u201cHopper GPU\u201d), \u201cenabling all CPU and GPU threads to access\n\nall system-allocated memory.\u201d The CPU is depicted as coupled to the GPU via \u201cNVLINK C2C\n\n[chip-to-chip],\u201d and can access the \u201cSystem Page Table\u201d and \u201cCPU PHYSICAL MEMORY\u201d via\n\n\u201cCPU-resident access\u201d and \u201cGPU PHYSICAL MEMORY\u201d via \u201c[r]emote access\u201d and \u201cPTE [page\n\ntable entry] B.\u201d The GPU can also access the System Page Table, and it can access \u201cGPU\n\nPHYSICAL MEMORY\u201d via \u201cGPU-resident access\u201d and \u201cCPU PHYSICAL MEMORY\u201d via\n\n\u201c[r]emote access\u201d and \u201cPTE A.\u201d Moreover, the \u201cSystem Page Table\u201d \u201c[t]ranslates CPU malloc()\n\n\n 74\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 76 75\n of 95\n of 94\n\n\n\n\n[memory allocation] to CPU or GPU.\u201d \u201cThe CPU heap, CPU thread stack, global variables\n\nmemory-mapped files, and inter-process memory are accessible to all CPU and GPU threads.\u201d\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 147. The \u201cCUDA programming model\u201d implements programming functions and\n\ninstructions for CPUs and GPUs. \u201cThe host is the CPU available in the system\u201d and \u201csystem\n\nmemory associated with the CPU is called host memory.\u201d \u201cThe GPU is called a device and GPU\n\nmemory likewise called device memory.\u201d As an example, the first main CUDA program execution\n\nstep is \u201c[c]opy[ing] the input data from host [CPU] memory to device [GPU] memory, also known\n\nas host-to-device transfer.\u201d\n\n\n\n\n 75\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 77 76\n of 95\n of 94\n\n\n\n\n(See https://developer.nvidia.com/blog/cuda-refresher-cuda-programming-model/ (emphasis\n\nadded).)\n\n 148. The Accused Products perform a method that includes executing, by the processing\n\nunit, a computational stream, the computational stream controlling data exchange between the\n\nuser interaction stream and the computational stream during execution of the computations\n\nrepresenting the artificial neural network. For instance, the \u201cCUDA programming model\u201d\n\nimplements programming functions and instructions for CPUs and GPUs. As previously stated,\n\nthe host is the CPU and the device is the GPU. After \u201c[c]opy[ing] the input data from host [CPU]\n\nmemory to device [GPU] memory,\u201d the second main CUDA program execution step is\n\n\u201c[l]oad[ing] the GPU program and execut[ing].\u201d\n\n\n\n\n 76\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 78 77\n of 95\n of 94\n\n\n\n\n(See https://developer.nvidia.com/blog/cuda-refresher-cuda-programming-model/ (emphasis\n\nadded).)\n\n 149. Indeed, the Grace Hopper Superchip \u201cis designed to accelerate applications\u201d using\n\n\u201cExtended GPU Memory.\u201d As depicted in the gram of the Grace Hopper architecture below, a\n\nGPU (\u201cHOPPER GPU\u201d) can access \u201cLocal CPU,\u201d \u201cPeer CPU,\u201d and \u201cPeer GPU\u201d memory via\n\n\u201cNVLink.\u201d\n\n\n\n\n 77\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 79 78\n of 95\n of 94\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 150. For instance, exemplary CUDA library cuDNN function\n\n\u201ccudnnSetRNNDescriptor_v8\u201d \u201cinitializes a previously created RNN [recurrent neural network]\n\ndescriptor object.\u201d This function \u201cstore[s] all information needed to compute the total number of\n\nadjustable weights/biases in the RNN model.\u201d In addition, the parameters \u201cdirMode,\u201d\n\n\u201cinputMode,\u201d and \u201cdatatype\u201d confirm the exchange of calculations and values between the hidden\n\nlayers of an RNN.\n\n\n\n\n *****\n\n\n\n\n 78\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 80 79\n of 95\n of 94\n\n\n\n\n(See https://docs.nvidia.com/deeplearning/cudnn/archives/cudnn-891/pdf/cuDNN-API.pdf\n\n(emphasis added).)\n\n 151. The Accused Products perform a method that includes shifting control of a data\n\nexchange between the user interaction stream and the computational stream to the computational\n\nstream in response to starting execution of the computations representing the artificial neural\n\nnetwork. For instance, the \u201cCUDA programming model\u201d implements programming functions and\n\ninstructions for CPUs (host) and GPUs (device). As an example, the \u201chost-to-device transfer\u201d\n\n(CPU to GPU) first main step, the second main step is \u201c[l]oad the GPU program and execute\u201d and\n\nthe third main step is \u201c[c]opy the results from device [GPU] memory to host [CPU] memory, also\n\nknown as device-to-host transfer\u201d (GPU to CPU).\n\n\n\n\n 79\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 81 80\n of 95\n of 94\n\n\n\n\n(See https://developer.nvidia.com/blog/cuda-refresher-cuda-programming-model/ (emphasis\n\nadded.)\n\n 152. As previously stated, the Grace Hopper Superchip \u201cis designed to accelerate\n\napplications\u201d using \u201cExtended GPU Memory\u201d and the GPU can access local/peer CPU and peer\n\nGPU memory via \u201cNVLink.\u201d The Grace Hopper Superchip\u2019s Extended GPU Memory feature\n\n\u201cenables GPUs to access all the system memory efficiently\u201d and \u201cphysical memory in the system\n\ncan be allocated to be accessible from any GPU thread.\u201d\n\n\n\n\n 80\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 82 81\n of 95\n of 94\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 153. The Accused Products perform a method that includes shifting control of the data\n\nexchange between the user interaction stream and the computational stream to the user interaction\n\nstream in response to completion or interruption of the computations representing the artificial\n\nneural network. For instance, after the \u201cCUDA programming model\u201d \u201chost-to-device transfer\u201d\n\n(CPU to GPU) and GPU program load and execution steps, the third main step is \u201c[c]opy the\n\nresults from device [GPU] memory to host [CPU] memory, also known as device-to-host transfer\u201d\n\n(GPU to CPU). The \u201chost-to-device transfer\u201d (CPU to GPU) first main step can be reintroduced\n\nfor additional computations.\n\n\n\n\n(See https://developer.nvidia.com/blog/cuda-refresher-cuda-programming-model/ (emphasis\n\n\n 81\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 83 82\n of 95\n of 94\n\n\n\n\nadded.)\n\n 154. In addition, as shown in the Grace Hopper Superchip architecture diagram below,\n\nthe CPU (\u201cGRACE CPU\u201d) \u201cshare[s] a single per-process page table\u201d with a GPU (\u201cHopper\n\nGPU\u201d), \u201cenabling all CPU and GPU threads to access all system-allocated memory.\u201d \u201cThe CPU\n\nheap, CPU thread stack, global variables memory-mapped files, and inter-process memory are\n\naccessible to all CPU and GPU threads.\u201d\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n 155. The Accused Products perform a method that includes queueing a user command\n\nreceived by the user interaction stream during execution of the computations representing the\n\nartificial neural network. For instance, as shown by publicly available CUDA toolkit\n\n\n\n 82\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 84 83\n of 95\n of 94\n\n\n\n\ndocumentation, CUDA implements exemplary \u201cmemory management functions\u201d that \u201c[c]op[y]\n\ndata between host [CPU] and device [GPU].\u201d This includes CUDA functions \u201ccudaMemcpy\u201d and\n\n\u201ccudaMemcpyAsync.\u201d\n\n\n\n\n *****\n\n\n\n\n *****\n\n\n\n\n(See https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__MEMORY.html\n\n(emphasis added).)\n\n 156. As an example, exemplary CUDA memory management function\n\n\u201ccudaMemcpyAsync\u201d \u201c[c]opies count bytes [data] from the memory area pointed to by src [source\n\nmemory address pointer] to the memory area pointed to by dst [destination memory address\n\npointer], where kind [type of transfer] specifies the direction of the copy.\u201d Destinations includes\n\n\u201ccudaMemcpyHostToDevice [CPU to device GPU], cudaMemcpyDeviceToHost [GPU to CPU],\n\ncudaMemcpyDeviceToDevice [GPU to GPU]. Because the function \u201ccudaMemcpyAsync() is\n\nasynchronous with respect to the host, [] the call may return before the copy is complete. The copy\n\ncan optionally be associated to a stream [identified stream] by passing a non-zero stream\n\nargument.\u201d\n\n\n\n\n 83\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 85 84\n of 95\n of 94\n\n\n\n\n(See https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__MEMORY.html\n\n(emphasis added).)\n\n 157. The Accused Products perform a method that includes executing the user command\n\nduring execution of the computations representing the artificial neural network at times\n\ndetermined by the computational stream. For instance, as shown by exemplary and publicly\n\navailable CUDA toolkit documentation, CUDA implements \u201cmemory management functions\u201d that\n\n\u201c[c]op[y] data between host [CPU] and device [GPU].\u201d\n\n\n\n\n 84\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 86 85\n of 95\n of 94\n\n\n\n\n *****\n\n\n\n\n *****\n\n\n\n\n(See https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__MEMORY.html\n\n(emphasis added).)\n\n 158. As an example, exemplary CUDA memory management function\n\n\u201ccudaMemcpyAsync\u201d \u201c[c]opies count bytes [data] from the memory area pointed to by src [source\n\nmemory address pointer] to the memory area pointed to by dst [destination memory address\n\npointer], where kind [type of transfer] specifies the direction of the copy.\u201d Because the function\n\n\u201ccudaMemcpyAsync() is asynchronous with respect to the host, [] the call may return before the\n\ncopy is complete. The copy can optionally be associated to a stream [identified stream].\u201d\n\n\n\n\n 85\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 87 86\n of 95\n of 94\n\n\n\n\n(See https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__MEMORY.html\n\n(emphasis added).)\n\n 159. In another example, CUDA implements \u201cCUDA-specific memory APIs [that]\n\nprovide users with guarantees about where the memory resides, which threads can access it,\n\nwhether it is migratable, and many other features that enable users to extract all the performance\n\nthe hardware has to offer.\u201d\n\n\n\n\n(See https://resources.nvidia.com/en-us-grace-cpu/nvidia-grace-hopper (emphasis added).)\n\n\n 86\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 88 87\n of 95\n of 94\n\n\n\n\n 160. Each claim in the \u2019461 Patent recites an independent invention. Neither claim 21,\n\ndescribed above, nor any other individual claim is representative of all claims in the \u2019461 Patent.\n\n 161. Defendant has been aware of the \u2019461 Patent since at least the filing of the original\n\nComplaint. Defendant has been aware of the technology patented by the \u2019461 Patent since at least\n\n2007, when the inventors of the Asserted Patents first discussed their patented technologies with\n\nMr. Sanford Russell, then the CTO of Nvidia. At the time, the inventors asked Defendant to\n\ncollaborate with them on training neural networks using Nvidia\u2019s GPUs. Defendant informed the\n\ninventors, through Mr. Russell, that it was not interested in the collaboration. Defendant has also\n\ncited an ancestor of the \u2019461 Patent in its own patent portfolio since at least June 28, 2010 (See\n\nhttps://patents.google.com/patent/US8648867B2/en?oq=8648867#citedBy;\n\nhttps://patentimages.storage.googleapis.com/ee/13/e9/61df149c3fddc7/US8922566.pdf;\n\nhttps://patentcenter.uspto.gov/applications/13335850/displayReferences/referenceForms?applicat\n\nion= (Nvidia U.S. Appl. No. 13/335,850 August 12, 2014, List of References Cited by Examiner).)\n\n 162. Starting in or around 2016, the inventors of the Asserted Patents held multiple\n\ndiscussions with Nvidia to invest in or purchase their AI company, Neurala, Inc., and all its assets,\n\nincluding the \u2019461 Patent family. These discussions included at least Mr. Alvin Lin, an Nvidia\n\nSenior Director of Business Development, and Mr. Jeff Herbst, then an Nvidia Vice President of\n\nBusiness Development and head of Nvidia\u2019s Inception GPU Ventures, in or around September 6,\n\n2016. In or around October 2016, Nvidia, through its representatives, initiated discussions with\n\nthe inventors to invest in Neurala, Inc. for approximately $10 million.\n\n 163. The inventors also discussed their patented technology, including the underlying\n\ntechnology and family to the \u2019461 Patent, with Defendant\u2019s representatives at Nvidia\u2019s artificial\n\nintelligence conference in or around June 2017. On or about June 26, 2017, Defendant received\n\n\n\n\n 87\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 89 88\n of 95\n of 94\n\n\n\n\nmaterials from the inventors, in lieu of a meeting on or about June 29, that identified patents related\n\nto the \u2019461 Patent and described the technology in detail. Defendant had previously stated it was\n\ninterested in the inventors\u2019 solutions. Defendant also featured the inventors on its website as\n\nmembers of Defendant\u2019s start-up incubator on or about September 25, 2019.\n\n\n\n\n *****\n\n\n\n\n(See https://developer.nvidia.com/blog/inception-spotlight-ai-startup-neurala-sees-7x-speedup-\n\nwith-ngc/ (September 25, 2019); see also https://www.youtube.com/watch?v=-WBtxGLoQNs\n\n(\u201cNeurala Accelerating AI Video Annotation with NGC Containers\u201d posted by Defendant\u2019s\n\nYouTube account).)\n\n 164. Neural AI and/or its predecessors-in-interest have satisfied all statutory obligations\n\nrequired to collect pre-filing damages for the full period allowed by law for infringement of the\n\n\u2019461 Patent.\n\n 165. Defendant directly infringes at least claim 21 of the \u2019461 Patent, either literally or\n\nunder the doctrine of equivalents, by performing the steps described above. For example,\n\nDefendant performs the claimed method in an infringing manner as described above by\n\n\n 88\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 90 89\n of 95\n of 94\n\n\n\n\nimplementing the Accused Products as part of its accelerated computing operations and running\n\ncorresponding software that implements the infringing performance. Defendant also performs the\n\nclaimed method in an infringing manner when testing the operation of the Accused Products and\n\ncorresponding systems. As another example, Defendant performs the claimed method when\n\nproviding or administering services to third parties, customers, and partners using the Accused\n\nProducts.\n\n 166. Defendant\u2019s partners, customers, and users of its Accused Products and\n\ncorresponding systems and services directly infringe at least claim 21 of the \u2019461 Patent, literally\n\nor under the doctrine of equivalents, at least by using the Accused Products and corresponding\n\nsystems and services, as described above.\n\n 167. Defendant has actively induced and is actively inducing infringement of at least\n\nclaim 21 of the \u2019461 Patent with specific intent to induce infringement, and/or willful blindness to\n\nthe possibility that its acts induce infringement, in violation of 35 U.S.C. \u00a7 271(b). For example,\n\nDefendant encourages and induces customers to use Nvidia\u2019s CUDA platform in a manner that\n\ninfringes claim 21 of the \u2019461 Patent at least by offering and providing software that performs a\n\nmethod that infringes claim 21 when installed and operated by the customer using the Accused\n\nProducts, and by engaging in activities relating to selling, marketing, advertising, promotion,\n\ninstallation, support, and distribution of the Accused Products.\n\n 168. Defendant encourages, instructs, directs, and/or requires third parties\u2014including\n\nits certified partners and/or customers\u2014to perform the claimed method using the software,\n\nplatform, services, and systems in infringing ways, as described above.\n\n 169. Defendant further encourages and induces its customers to infringe claim 21 of the\n\n\u2019461 Patent: 1) by making its accelerated computing and data center services available on its\n\n\n\n\n 89\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 91 90\n of 95\n of 94\n\n\n\n\nwebsite, providing applications that allow users to access those services, widely advertising those\n\nservices, and providing technical support and instructions to users (see\n\nhttps://www.nvidia.com/en-us/data-center/data-center-gpus/gpu-test-drive/); and 2) through\n\nactivities relating to marketing, advertising, promotion, installation, support, and distribution of\n\nthe Accused Products, including its CUDA platform, and services in the United States. (See\n\nhttps://www.nvidia.com/en-us/; see https://www.nvidia.com/en-us/about-nvidia/partners/;\n\nhttps://www.nvidia.com/en-us/data-center/where-to-buy/; https://www.nvidia.com/en-us/data-\n\ncenter/where-to-buy-tesla/.)\n\n 170. For example, Defendant shares instructions, guides, and manuals, which advertise\n\nand instruct third parties on how to use its hardware and platform as described above, including at\n\nleast customers and partners. (See https://docs.nvidia.com/cuda/cuda-c-programming-guide/.)\n\nDefendant also provides customer service and technical support to purchasers of the Accused\n\nProducts and corresponding systems and services, which directs and encourages customers to\n\nperform certain actions that use the Accused Products in an infringing manner. (See\n\nhttps://www.nvidia.com/en-us/support/; https://www.nvidia.com/en-\n\nus/support/enterprise/services/.)\n\n 171. Defendant and/or Defendant\u2019s partners recommend and sell the Accused Products\n\nand provide technical support for the installation, implementation, integration, and ongoing\n\noperation of the Accused Products for each individual customer. On information and belief, each\n\ncustomer enters into a contractual relationship with Defendant and/or one of Defendant\u2019s partners,\n\nwhich obligates each customer to perform certain actions in order to use the Accused Products.\n\n(See https://www.nvidia.com/en-us/agreements/; https://www.nvidia.com/en-\n\nus/agreements/cloud-services/nvidia-cloud-agreement/; https://www.nvidia.com/en-\n\n\n\n\n 90\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 92 91\n of 95\n of 94\n\n\n\n\nus/agreements/cloud-services/service-specific-terms-for-nvidia-dgx-cloud/.) Further, in order to\n\nreceive the benefit of Defendant\u2019s and/or its partner\u2019s continued technical support and their\n\nspecialized knowledge and guidance of the operability of the Accused Products, each customer\n\nmust continue to use the Accused Products in a way that infringes the \u2019461 Patent. (See\n\nhttps://www.nvidia.com/en-us/support/.)\n\n 172. Further, as the entity that provides installation, implementation, and integration of\n\nthe Accused Products in addition to ensuring the Accused Product remains operational for each\n\ncustomer through ongoing technical support, on information and belief, Defendant and/or\n\nDefendant\u2019s partners affirmatively aid and abet each customer\u2019s use of the Accused Products in a\n\nmanner that performs the claimed method of, and infringes, the \u2019461 Patent.\n\n 173. Defendant also contributes to the infringement of its partners, customers, and users\n\nof the Accused Products by providing within the United States or importing into the United States\n\nthe Accused Products, which are for use in practicing, and under normal operation practice, the\n\nmethods, systems, and devices claimed in the Asserted Patents, constituting a material part of the\n\ninventions claimed, and not a staple article or commodity of commerce suitable for substantial\n\nnon-infringing uses. Indeed, as shown above, the Accused Products and the example functionality\n\nhave no substantial non-infringing uses but are specifically designed to practice the \u2019461 Patent.\n\n 174. On information and belief, the infringing actions of each partner, customer, and/or\n\nuser of the Accused Products are attributable to Defendant. For example, on information and belief,\n\nDefendant directs and controls the activities or actions of its partners or others in connection with\n\nthe Accused Products by contractual agreement or otherwise requiring partners or others to provide\n\ninformation and instructions to customers who acquire the Accused Products which, when\n\nfollowed, results in infringement. Defendant further directs and controls the operation of devices\n\n\n\n\n 91\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 93 92\n of 95\n of 94\n\n\n\n\nexecuting the Accused Products by programming the software which, when executed by a\n\ncustomer or user, performs the claimed method of at least claim 21 of the \u2019461 Patent.\n\n 175. Plaintiff has suffered and continues to suffer damages as a result of Defendant\u2019s\n\ninfringement of the \u2019461 Patent. Defendant is therefore liable to Plaintiff under 35 U.S.C. \u00a7 284\n\nfor damages in an amount that adequately compensates Plaintiff for Defendant\u2019s infringement, but\n\nno less than a reasonable royalty.\n\n 176. Defendant\u2019s infringement of the \u2019461 Patent is knowing and willful. Defendant\n\nacquired actual knowledge of the family of the \u2019461 Patent since at least 2017 and has acquired\n\nadditional knowledge of the \u2019461 Patent since at least the filing of this lawsuit.\n\n 177. On information and belief, despite Defendant\u2019s knowledge of the Asserted Patents and\n\nPlaintiff\u2019s patented technology, Defendant made the deliberate decision to sell products and services\n\nthat it knew infringe these patents. Defendant\u2019s continued infringement of the \u2019461 Patent with\n\nknowledge of the \u2019461 Patent constitutes willful infringement.\n\n\n\n\n 92\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 94 93\n of 95\n of 94\n\n\n\n\n PRAYER FOR RELIEF\n\nWHEREFORE, Plaintiff respectfully requests the following relief:\n\n a) That this Court adjudge and decree that Defendant has been, and is currently,\n\n infringing each of the Asserted Patents;\n\n b) That this Court award Plaintiff damages to compensate for Defendant\u2019s past and\n\n future infringement of the Asserted Patents, through the life of the Asserted Patents;\n\n c) That this Court award Plaintiff pre- and post-judgment interest on such;\n\n d) That this Court order an accounting of damages incurred by Plaintiff from six years\n\n prior to the date this lawsuit was filed through entry of a final, non-appealable\n\n judgment;\n\n e) That this Court determine that this patent infringement case is exceptional and\n\n award Plaintiff its costs and attorneys\u2019 fees incurred in this action;\n\n f) That this Court award increased damages under 35 U.S.C. \u00a7 284; and\n\n g) That this Court award such other relief as the Court deems just and proper.\n\n DEMAND FOR JURY TRIAL\n\n Plaintiff respectfully requests a trial by jury on all issues triable thereby.\n\n\n\n\n 93\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-2 30 Filed\n Filed\n 08/18/26\n 12/12/24 Page\n Page\n 95 94\n of 95\n of 94\n\n\n\nDATED: December 12, 2024\n By:/s/ Mark D. Siegmund\n Mark D. Siegmund\n Texas Bar No. 24117055\n CHERRY JOHNSON SIEGMUND JAMES\n PLLC\n Bridgeview Center\n 7901 Fish Pond Road, 2nd Floor\n Waco, Texas 76710\n Telephone: (254) 732-2242\n Facsimile: (866) 627-3509\n msiegmund@cjsjlaw.com\n\n Christopher C. Campbell\n KING & SPALDING LLP\n 1700 Pennsylvania Avenue, NW\n Suite 900\n Washington, DC 20006\n Telephone: (202) 626-5578\n Facsimile: (202) 626-3737\n ccampbell@kslaw.com\n\n Britton F. Davis\n Brian Eutermoser (pro hac vice to be filed)\n KING & SPALDING LLP\n 1401 Lawrence Street\n Suite 1900\n Denver, CO 80202\n Telephone: (720) 535-2300\n Facsimile: (720) 535-2400\n bfdavis@kslaw.com\n beutermoser@kslaw.com\n\n Attorneys for Plaintiff Neural AI, LLC\n\n\n CERTIFICATE OF SERVICE\n\n The undersigned does hereby certify that a true and correct copy of the foregoing document\n\nwas served on all counsel of record via the Court\u2019s electronic filing system on this 12th day of\n\nDecember 2024.\n\n By:/s/ Mark D. Siegmund\n Mark D. Siegmund\n\n\n\n 94\n\f","ocr_status":2,"date_upload":"2026-08-20T10:55:12.845790-07:00","document_number":"1","attachment_number":2,"pacer_doc_id":"181037219897","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 1","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514516/","id":490514516,"tags":[],"absolute_url":"/docket/74667129/1/3/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:12.999676-07:00","date_modified":"2026-08-23T02:41:31.239684-07:00","sha1":"0870b13f3bc787fd8856ec813c6c7c60ce89f0b1","page_count":15,"file_size":1311109,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.3.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.3.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-3 Filed 08/18/26 Page 1 of 15\n\n\n\n\n EXHIBIT\n\n 2\n\f Case 7:26-mc-00324-DC Document 1-3 Filed 08/18/26 Page 2 of 15\n\n USOO8648867B2\n\n\n(12) United States Patent (10) Patent No.: US 8,648,867 B2\n Gorchetchnikov et al. (45) Date of Patent: Feb. 11, 2014\n(54) GRAPHIC PROCESSORBASED (56) References Cited\n ACCELERATOR SYSTEMAND METHOD\n U.S. PATENT DOCUMENTS\n(75) Inventors: Anatoli Gorchetchnikov, Belmont, MA 5,388,206 A * 2/1995 Poulton et al. ................ 345,505\n (US); Heather Marie Ames, South 2005, 0166042 A1* 7, 2005 Evans ............ T13,150\n Boston, MA (US); Massimiliano 2007/0052713 A1* 3/2007 Chung et al. ... 34.5/5O1\n Versace, South Boston, MA (US); 2007/0279429 A1* 12/2007 Ganzer ......................... 345,582\n Fabrizio Santini, Jamaica Plain, MA\n (US) * cited by examiner\n(73) Assignee: Neurala LLC, Boston, MA (US) Primary Examiner \u2014 Maurice L. McDowell, Jr.\n(*) Notice: Subject to any disclaimer, the term of this (57) ABSTRACT\n patent is extended or adjusted under 35 An accelerator system is implemented on an expansion card\n U.S.C. 154(b) by 1030 days. comprising a printed circuit board having (a) one or more\n graphics processing units (GPU), (b) two or more associated\n(21) Appl. No.: 11/860,254 memory banks (logically or physically partitioned), (c) a\n(22) Filed: Sep. 24, 2007 specialized controller, and (d) a local bus providing signal\n coupling compatible with the PCI industry standards (this\n(65) Prior Publication Data includes but is not limited to PCI-Express, PCI-X, USB 2.0,\n or functionally similar technologies). The controller handles\n US 2008/O 117220 A1 May 22, 2008 most of the primitive operations needed to set up and control\n Related U.S. Application Data GPU computation. As a result, the computer's central pro\n cessing unit (CPU) is freed from this function and is dedicated\n(60) Provisional application No. 60/826,892, filed on Sep. to other tasks. In this case a few controls (simulation start and\n 25, 2006. stop signals from the CPU and the simulation completion\n signal back to CPU), GPU programs and input/output data are\n(51) Int. C. the information exchanged between CPU and the expansion\n G06F 5/00 (2006.01) card. Moreover, since on every time step of the simulation the\n(52) U.S. C. results from the previous time step are used but not changed,\n USPC ........................................... 345/501; 34.5/503 the results are preferably transferred back to CPU in parallel\n(58) Field of Classification Search with the computation.\n USPC .................................................. 345/501,503\n See application file for complete search history. 19 Claims, 5 Drawing Sheets\n\n 140 200\n 8O 250\n -4\n\n\n SHADERE.K.\n MEMORY\n\n 50\n\n O EXRE\n - icon TROLLER w NEMORY\n\n C\n -\n\n\n\n\n 2\n\f Case 7:26-mc-00324-DC Document 1-3 Filed 08/18/26 Page 3 of 15\n\n\nU.S. Patent Feb. 11, 2014 Sheet 1 of 5 US 8,648,867 B2\n\n\n\n\n 7.\n\n\n\n\n $3.\n\n\n\n\n s\n\n\n\n\n FG,\n\f Case 7:26-mc-00324-DC Document 1-3 Filed 08/18/26 Page 4 of 15\n\n\nU.S. Patent Feb. 11, 2014 Sheet 2 of 5 US 8,648,867 B2\n\n\n\n\n g\n i.\n :\n i\n : r\n s\n al e3esiasti Od\n\n\n s\n\n 3\n\n\n s\n\f Case 7:26-mc-00324-DC Document 1-3 Filed 08/18/26 Page 5 of 15\n\n\nU.S. Patent Feb. 11, 2014 Sheet 3 of 5 US 8,648,867 B2\n\n\n\n\n 300\n CPU 120 Start\n 304\n Expansion Cardiso :\n iaia fict iss: Risitio: &::::::::8:::::::::\n Sires 301 Se::303\n 320\n Disk:O Graphic User Controller\n Interface initialization\n initialization Initialization\n\n\n\n\n 325\n User input Parser External input\n Texture textures from RAM to\n interaction Generator texture memory bank\n 326 :\n Population Parser Population shader\n Shader Generato binaries from RAM to\n and Compiler shader memory bank\n\n\n\n\n Simulation\n Initialization\n\n\n 330\n\n\n Progress Input Parser\n monitor Texture\n Generator Computation\n (see Fig. 4)\n Data output\n to Disk\n Output Data Data\n ACCumulation issils\n in RAM\n\n Last\n iteration\n 318 :\n\n Yes\n 350\n\n\n\n\n 3\n\f Case 7:26-mc-00324-DC Document 1-3 Filed 08/18/26 Page 6 of 15\n\n\nU.S. Patent Feb. 11, 2014 Sheet 4 of 5 US 8,648,867 B2\n\n\n Expansion Card 180\n\n Simulation\n start\n\n iDesi: {34}{ut : {iciplisiii) 2. iaia iiii:\n Si:Sires: Siii:Sire:: Silisirai?\n 402 403 404\n Input textures from\n texture memory\n bank to GPU\n\n\n\n Shaders from\n shader memory\n bank to GPU\n\n\n ... ...........\n\n\n\n\n Shader\n execution\n\n\n\n\n Output texture\n upload to texture\n memory bank\n\n New external input Data\n textures from RAM told -----------\n\n\n\n\n Wait for swap Swap input Wait for swap\n of input/output and output of input/output\n texture pointers texture pointers texture pointers\n\n 475\n Input textures from NO Last\n texture memory iteration?\n bank to RAM\n Yes\n\n\n\n iteration?\n Yes 490\n Wait for all three\n streams of\n execution to finish\n\n 499\n\n\n\n EIG 4\n\f Case 7:26-mc-00324-DC Document 1-3 Filed 08/18/26 Page 7 of 15\n\n\nU.S. Patent Feb. 11, 2014 Sheet 5 of 5 US 8,648,867 B2\n\n\n\n\n (p)\n\n\n\n\n *\u00b7,,?)&xaddO2OInputDependency(m gate1, O., O., 0.004, O., 0, 0);\nInteraction Stream, Data Output Stream, and Computational u->addFullDependency(m gate2, population());\nStream. Through TSimulator:timestep(), TSimulator:out 40\nfileInterval ( ), and TSimulator:outmode(), the application public: TCablePopRCF(): TPopulation(\u201ccompCPU RCF, w, h, true)\ncan set the time step of the simulation, the time step of disk { };\noutput, and the mode of the disk output. The external input ~TCablePopRCF() {if(m equation) delete m equation;\n if(m gate1) delete m gate1;\npattern should be packed into a TPattern object and bound to\nthe simulation object through TSimulator:resetInputs( ) 45 bool if(m gate2) delete m gate2:};\n fillElements(TSimulator sim);\nmethod. TSimulator::simLength( ) sets the length of the }:\nsimulation. bool TCablePopRCF::fillElements(TSimulatior sim)\n The second step is to create at least one population of { equation = new TEq RCF (this, m compet, m persist);\nequations (TPopulation object). Population holds one equa mcreateCatingStructure();\ntion object TEquation. This object contains only a formula 50 for(size ti = 0; i < x.Size(); ++i)\nand does not hold element-specific data, so all elements of the for(size tj = 0; j < ySize(); ++)\npopulation can share single TEquation. {\n The TEquation object is converted to a GPU program TElement u = new TCPUElement(this, m equation, i,j):\n sim->addUnit(u);\nbefore execution. GPU programs have to be executed within createUnitStructure(u);\na graphical context, which is stream specific. TSimulator 55 return true:\ncreates this context within a Computational Stream, therefore\nall programs and data arrays that are necessary for computa int\ntion have to be initialized within Computational Stream. Con main()\nstructor of TPopulation is called from User Interaction //{ Input pattern generation (309 in FIG. 3)\nStream, so no GPU-related objects can be initialized in this 60 uint32 t pat = new uint32 twh;\nCOnStructOr. TRandom-float randGen (O);\n TPopulation::fillElements( ) is a virtual method designed for(uint32 ti = 0; i < wh; ++i)\nto overcome this difficulty. It is called from within the Com pati = randGen.random ();\nputational Stream after TSimulator::networkCreate( ) is TPattern p = new TPattern (pat, w, h);\n if Setting up the simulation\ncalled in the User Interaction Stream. A user has to override 65 TSimulator cableSim = new TSimulator(\u201cdata'); fi(308 and 320 in\nTPopulation::fillElements( ) to create TEquation and other FIG. 3)\ncomputation related objects both element independent and\n\f Case 7:26-mc-00324-DC Document 1-3 Filed 08/18/26 Page 13 of 15\n\n\n US 8,648,867 B2\n 11 12\n -continued need to perform the computations and initiates the upload 435\n of them onto the GPU 240. The GPU 240 can communicate\ncableSim->timestep(0.05); fi(320 in FIG. 3)\ncableSim->resetInputs(p); (325 in FIG. 3) directly with the texture memory bank 250 to upload the\ncableSim->OutfileInterval(0.1); (308 in FIG. 3) appropriate texture to perform the computations. The control\ncableSim->Outmode(SANNDRA::timefunc); (308 in FIG. 3)\ncableSim->simLength(60.0); (320 in FIG. 3)\n ler 220 also pulls the first shader (known by the stored order)\nif Preparing the population from the shader memory bank 210 and uploads 450 it onto the\nTPopulation* cablePop = new TCablePopRCF(); //(310 in FIG. 3) GPU 240.\ncableSim->networkCreate(); //(326 in FIG. 3) The GPU 240 executes the following operations in this\nuint16 t user = 1; order: performs the computation (execution of the shader)\nwhile(user) 10\n 470; tells the controller 220 that it is done with the computa\nif(cableSim->simulationStart(true, 1)) (311 in FIG. 3) tions for the current shader; and after all shaders for this\nexit(1): particular equation are executed sends 480 the output textures\nstd::cout-\u201cRepeat?\\n: //(305 in FIG. 3)\nstd::cin>user; //(305 in FIG. 3) to the output portion of the texture memory bank 250. This\nif(user == 1) 15 cycle continues through all of the equations based on the\ncableSim->networkReset(); //(305 in FIG. 3) branching step 482.\nif cableSim) An example shader that performs fourth order Runge\ndelete cableSim; Also deletes cablePop and its internals Kutta numerical integration is shown in Listing 2 using GLSL\nexit(0); notation;\nListing 1.\n\n FIG. 4 is a detailed flow diagram illustrating a part of an uniform sampler2DRect Variable;\n uniform float integration step;\nexemplary implementation of the bottom level system and float halfstep = integration step*0.5;\nmethod performed during the computation on the GPU accel 25 float fl. 6 step = integration stepf 6.0:\nerator of the expansion card 180 and is a more detailed view vec4 output = texture2DRect(Variable, gl TexCoord O.st);\n if define equation() here\nof the computational box 330 in FIG. 3. FIG. 4 is a represen vec4 rungekutta4(vec4 x)\ntation of one of several ways in which a system and method\nfor processing numerical techniques can be implemented. const vecA k1 = equation(x);\n const vec4 k2 = equation(x + halfstep*k1);\n With systems of equations that have complex interdepen 30 const vec4 k3 = equation(x + halfstep*k2);\ndencies it is likely that the variable in Some equation from a const vecA k4 = equation(x + integration Step*k3);\nprevious time step has to be used by some other equation after return fl. 6step*(k1 + 2.0* (k2 + k3) + k4);\nthe new values of this variable are already computed for new\ntime step. To avoid data confusion, the new values of variables void main (void)\n {\nshould be rendered in a separate texture. After the time step is 35 output += rungekutta4(output);\ncompleted for all equations, these new values should be cop gl FragColor = output;\nied over old values so that they are used as input during the Listing 2.\nnext time step. Copying textures is an expensive operation,\ncomputationally, but since the textures are referred to by\ntexture IDs (pointers), Swapping these pointers for input and 40 The shader in Listing 2 can be executed on conventional\noutput textures after each time step achieves the same resultat video card. Using the controller 220 this code can be further\na much lesser cost. optimized, however. Since the integration step does not\n In the hardware solution suggested herein, ID Swapping is change during the simulation, the step itself as well as the\nequivalent to Swapping the base memory address for two halfstep and /6 of the step can be computed once per simula\npartitions of the texture memory bank 250. They are swapped 45 tion, and updated in all shaders by a shader update procedures\n485 during synchronization (485, 430, and 455) so that data\ntransfer 445 and the computation 435-487 proceeds immedi 310,326 discussed above.\nately and in parallel with data transfer as shown in FIG. 4. A computed theofmain\n After all the equations in the computational cycle are\nhardware solution allows this parallelism through access of 220 can switch 485execution the\n substream 403 on the controller\n reference pointers of the input and\nthe controller 220 to the onboard texture memory bank 250. 50 output portions of the texture memory bank 250.\n The main computation and data exchange are executed by The two other substreams of execution on the controller\nthe controller 220. It runs three parallel substreams of execu\ntion: Computational Substream 403, Data Output Substream 220 are waiting (blocks 430 and 455, respectively) for this\n402, and Data Input Substream 404. These streams are syn switch to begin their execution. The Data Input Substream\nchronized with each other during the swap of pointers 485 to 55 404 is controlling 440 the input of additional data from the\nthe input and output texture memory partitions of the texture CPU 120. This is necessary in cases where the simulation is\nmemory bank 250 and the check for the last iteration 487. monitoring the changing input, for example input from a\nAlgorithmically, these two operations are a single atomic video camera or other recording device in the real time. This\noperation, but the block diagram shows them as two separate substream uploads new external input from the CPU 120 to\nblocks for clarity. 60 the texture memory bank 250 so it can be used by the main\n The Computational Substream 403 performs a computa computational Substream 403 on the next computational step\ntional cycle including a sequential execution of all shaders and waits for the next iteration 475. The Data Output Sub\nthat were stored in the shader memory bank 210 using the stream 445 controls the output of simulation results to the\nappropriate input and output textures. To begin the simulation CPU 120 if requested by the user. This substream uploads the\nthe controller 220 initializes three execution substreams 403, 65 results of the previous step to the main RAM 130 so that the\n402, and 404. On every simulation step, the Computational CPU 120 can save them on disk 140 or show them on the\nSubstream 403 determines which textures the GPU 240 will results display 313 and waits for the next iteration 460.\n\f Case 7:26-mc-00324-DC Document 1-3 Filed 08/18/26 Page 14 of 15\n\n\n US 8,648,867 B2\n 13 14\n Since the Computational Substream 403 determines the While this invention has been particularly shown and\ntiming of input 440 and output 445 data transfers, these data described with references to preferred embodiments thereof,\ntransfers are driven by the controller 220. To further reduce it will be understood by those skilled in the art that various\nthe data transfer overhead (and disk 140 overhead also) the changes in form and details may be made therein without\ncontroller 220 initiates transfer only after selected computa departing from the scope of the invention encompassed by the\ntional steps. For example, if the experimental data that is appended claims.\nsimulated was recorded every 10 milliseconds (msec) and the\nsimulation for better precision was computed every 1 mSec, What is claimed is:\nthen only every tenth result has to be transferred to match the 1. A computer system for performing a numerical simula\nexperimental frequency. 10 tion over a plurality of computational cycles including at least\n This solution stores two copies of output data, one in the a first computational cycle and a second computational cycle,\nexpansion card texture memory bank 250 and another in the the computer system comprising:\nsystem RAM 130. The copy in the system RAM 130 is a central processing unit;\naccessed twice: for disk I/O and screen visualization 313. An a main memory, operably coupled to the central processing\nalternative solution would be to provide CPU 120 with a 15 unit, to store input data to be accessed by the central\ndirect read access to the onboard texture memory bank 250 by processing unit in performing the numerical simulation;\nmapping the memory of the hardware onto a global memory a video system, operably coupled to the central processing\nspace. The alternative solution will double the communica unit, to drive a video monitor to display an indication of\ntion through the local bus 190. Since the goal discussed herein the numerical simulation in response to the computer\nis reducing the information transfer through the local bus 190, system performing the numerical simulation;\nthe former solution is favored. an accelerator, operably coupled to the central processing\n The main stream substream 403 determines if this is the last unit, to receive at least a portion of the input data from\niteration 487. If it is the last iteration, the controller 220 waits the central processing unit and to provide first output\nfor the all of the execution substreams to finish 490 and then data generated during the first computational cycle to the\nreturns the control to the CPU 120, otherwise it begins the 25 central processing unit after a conclusion of the first\nnext computational cycle. computational cycle, the accelerator comprising:\n This repeats through all of the computational cycles of the at least one graphics processing unit to generate second\nsimulation. output data, during the second computational cycle,\n Conclusion by performing at least one calculation on the first\n This GPU accelerator system offers the following potential 30 output data; and\nadvantages: an accelerator memory, operably coupled to the at least\n 1. Limited computations on the CPU 120. The CPU 120 is one graphic processing unit, the accelerator memory\nonly used for user input, sending information to the controller comprising:\n220, receiving output after each computational cycle (or less a first partition, referenced by a first pointer, to store\nfrequently as defined by the user), writing this output to disk 35 the first output data during the second computa\n140, and displaying this output on the monitor 170. This frees tional cycle; and\nthe CPU 120 to execute other applications and allows the a second partition, referenced by a second pointer, to\nexpansion card to run at its full capacity without being slowed store the second output data generated during the\ndown by extensive interactions with the CPU 120. second computational cycle; and\n 2. Minimizing data transfer between the expansion card 40 an accelerator controller, operably coupled to the accelera\n180 and the system bus 200. All of the information needed to tor memory and the central processing unit, to transfer\nperform the simulations will be stored on the expansion card the at least the portion of the input data into the accel\n180 and all simulations will take place on it. Furthermore, erator memory before the first computational cycle, to\nwhatever data transfer remains necessary will take place in transfer the first output data from the accelerator\nparallel with the computation, thus reducing the impact of this 45 memory to the main memory during the second compu\ntransfer on the performance. tational cycle, to direct the second output data into the\n 3. New way to execute GPU programs (shaders). Previ second partition during the second computational cycle,\nously, the CPU 120 had full control over the order of shaders and to Swap the first pointer and the second pointer at the\nexecution and was required to produce specific commands on conclusion of the second computational cycle Such that\nevery cycle to tell the GPU 240 which shader to use. With the 50 the second output data becomes an input for a third\ninvention disclosed herein, shaders will initially be stored on computational cycle of the plurality of computational\nthe shader memory bank 210 on the expansion card 180 and cycles.\nwill be sent to the GPU 240 for execution by the general 2. The computer system as claimed in claim 1, wherein the\npurpose controller 220 located on the expansion card. accelerator controller is configured to dictate an order of\n 4. Multiple parallelisms. The GPU 240 is inherently paral 55 execution of instructions to the at least one graphics process\nlel and is well suited to perform parallel computations. In ing unit.\nparallel with the GPU 240 performing the next calculation, 3. The computer system as claimed in claim 1, wherein the\nthe controller 220 is uploading the data from the previous accelerator controller comprises an interface controller to\ncalculation into main memory 130. Furthermore, the CPU communicate with the central processing unit over a bus of\n120 at the same time uses uploaded previous results to save 60 the computer system.\nthem onto disk 140 and to display them on the screen through 4. The computer system as claimed in claim 1, wherein the\nthe system bus 200. accelerator memory comprises a texture memory bank to\n 5. Reuse of existing and affordable technology. All hard store the at least the portion of the input data and the first\nware used in the invention and mentioned here-in are based on output data and a shader memory bank to store instructions\ncurrently available and reliable components. Further advance 65 for performing a set of operations to be performed on the at\nof these components will provide straightforward improve least the portion of the input data by the at least one graphic\nments of the invention. processing unit.\n\f Case 7:26-mc-00324-DC Document 1-3 Filed 08/18/26 Page 15 of 15\n\n\n US 8,648,867 B2\n 15 16\n 5. The computer system as claimed in claim 4, wherein the bank to store instructions for processing operations to be\ntexture memory is partitioned into the first partition, the sec performed on the input data by the at least one graphic pro\nond partition, a third partition to store internal variables, a cessing unit.\nfourth partition to store data textures used as input at a par 13. The accelerator system as claimed in claim 12, wherein\nticular computation cycle of the plurality of computational 5 the texture memory is partitioned into a first partition to store\ncycles. the input data, a second partition to store internal variables, a\n 6. The computer system as claimed in claim 1, wherein the third partition to store data textures used as input at a particu\naccelerator controller inputs the at least the portion of the lar computation cycle of the numerical simulation, and a\ninput data and a series of instructions into the at least one fourth partition to store the output data.\ngraphic processing unit, wherein the at least one graphics 10\nprocessing unit then executes the instructions on the at least the14. The accelerator system as claimed in claim 9, wherein\n accelerator controller is configured to perform successive\nthe portion of the input data. computational cycles of the numerical simulation by feeding\n 7. The computer system as claimed in claim 1, wherein the the output data generated\naccelerator controller comprises a set of instructions stored ing unit from a previous by the at least one graphic process\n computational cycle and the input\non a memory. 15\n 8. The computer system as claimed in claim 1, wherein the data for a next computational cycle into the at least one\nat least the portion of the input data represents an initial graphic processing unit.\ncondition of the numerical simulation. 15. The accelerator system as claimed in claim 9, wherein\n 9. An accelerator system for a computer system performing the accelerator controller comprises a set of instructions\na numerical simulation, the accelerator system comprising: 20 stored in a memory.\n 16. A method for performing a numerical simulation on\n at least one graphics processing unit to generate output data input data in a computer system including a central process\n by performing at least one computation during a first\n computational cycle of the numerical simulation; ing unit and an accelerator, the method comprising:\n an accelerator memory, operably coupled to the at least one receiving, by an accelerator, first input data from the central\n processing unit;\n graphics processing unit, to store data used to perform 25 transferring,\n the at least one computation; and by an accelerator controller, the first input\n an accelerator controller, operably coupled to the accelera data into a first partition, referenced by first pointer. ofan\n tor memory and the at least one graphics processing unit, accelerator memory before a first computational cycle of\n to execute: the numerical simulation;\n (i) a computational stream controlling performance of 30 performing, by at least one graphics processing unit during\n the first computational cycle, at least one calculation on\n the at least one computation by the at least one graph the first portion of the input data as to generate first\n ics processing unit; output data;\n (ii) an output stream controlling transfer of the output storing, by the accelerator controller, the first output data\n data from the at least one graphics processing unit to into a second partition, referenced by a second pointer,\n the accelerator memory during the first computational 35 of the accelerator memory; and\n cycle; and\n (iii) an input stream controlling transfer of input data to Swapping the first pointer with the second pointer at the end\n the accelerator memory for use by the at least one of the first computational cycle, such that the first output\n graphics processing unit during a second computa data becomes an input for a second computational cycle\n of the numerical simulation.\n tional cycle of the numerical simulation. 40\n 10. The accelerator system as claimed in claim 9, wherein 17. The method as claimed inclaim 16, further comprising:\nthe accelerator controller is configured to dictate an order of sending, by the accelerator controller, instructions for per\nexecution of instructions to the at least one graphics process forming the at least one calculation to the at least one\ning unit. graphics processing unit.\n 11. The accelerator system as claimed in claim 9, wherein 45 18. The method as claimed in claim 16, further comprising:\nthe accelerator controller is configured to send instructions to partitioning the accelerator memory into the first partition,\nthe at least one graphics processing unit, wherein the at least the second partition, a third partition to store internal\none graphics processing unit is configured to execute the Variables, and a fourth partition to store data used as\ninstructions on the input data, and wherein the accelerator input at a particular computation cycle of the numerical\n simulation.\ncontroller is configured to transfer the output data from the 50 19. The method of claim 16, further comprising:\naccelerator memory to a main memory during the execution transferring, by the accelerator controller, the first output\nof the instructions by the at least one graphics processing unit. data to the main memory during the second computa\n 12. The accelerator system as claimed in claim 9, wherein tional cycle.\nthe accelerator memory comprises a texture memory bank to\nStore the input data and the output data and a shader memory\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:12.788436-07:00","document_number":"1","attachment_number":3,"pacer_doc_id":"181037219898","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 2","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514517/","id":490514517,"tags":[],"absolute_url":"/docket/74667129/1/4/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.011698-07:00","date_modified":"2026-08-23T01:30:47.922117-07:00","sha1":"2a28da633ed025e43c0a6c20e4474fb00a691868","page_count":22,"file_size":2169754,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.4.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.4.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 1 of 22\n\n\n\n\n EXHIBIT\n\n 3\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 2 of 22\n\n USOORE48438E\n(( 1912)) United\n United States\n Reissued Patent ( 10 ) Patent Number : US RE48,438 E\n Gorchetchnikov et al . (45 ) Date of Reissued Patent : * Feb . 16, 2021\n( 54 ) GRAPHIC PROCESSOR BASED ( 56 ) References Cited\n ACCELERATOR SYSTEM AND METHOD\n U.S. PATENT DOCUMENTS\n( 71 ) Applicant: Neurala, Inc. , Boston, MA (US) 5,063,603 A 11/1991 Burt\n( 72 ) Inventors: Anatoli Gorchetchnikov , Belmont, MA 5,136,687 A 8/1992 Edelman et al .\n (US ) ; Heather Marie Ames , Milton , (Continued )\n MA (US ) ; Massimiliano Versace, FOREIGN PATENT DOCUMENTS\n Milton, MA (US ); Fabrizio Santini ,\n Jamaica Plain, MA (US) EP 1 224 622 B1 7/2002\n WO WO 2014/190208 11/2014\n( 73 ) Assignee : Neurala, Inc. , Boston, MA (US) ( Continued )\n( * ) Notice: This patent is subject to a terminal dis\n claimer . OTHER PUBLICATIONS\n( 21 ) Appl. No .: 15 /808,201 Cornwall et al . , \u201c Automatically Translating a General Purpose C ++\n Image Processing Library for GPUs \u201d , IEEE , Jun . 2006 , 8 pages .\n(22 ) Filed : Nov. 9 , 2017 ( Year: 2006 ) . *\n Related U.S. Patent Documents ( Continued )\nReissue of:\n( 64) Patent No .: 9,189,828 Primary Examiner William H. Wood\n Issued: Nov. 17 , 2015 (74 ) Attorney, Agent, or Firm -Smith Baluch LLP\n Appl. No .: 14 /147,015 ( 57 ) ABSTRACT\n Filed : Jan. 3 , 2014\nU.S. Applications: An accelerator system is implemented on an expansion card\n( 63 ) Continuation of application No. 11 / 860,254 , filed on comprising a printed circuit board having ( a) one or more\n Sep. 24 , 2007 , now Pat . No. 8,648,867 . graphics processing units ( GPUs ) , ( b ) two or more associ\n (Continued ) ated memory banks ( logically or physically partitioned ), (c )\n a specialized controller, and ( d) a local bus providing signal\n( 51 ) Int. Ci. coupling compatible with the PCI industry standards. The\n GO6T 1/60 ( 2006.01 ) controller handles most of the primitive operations to set up\n G06F 9/50 ( 2006.01 ) and control GPU computation. Thus, the computer's central\n (Continued ) processing unit ( CPU) can be dedicated to other tasks . In this\n( 52 ) U.S. Ci . case a few controls ( simulation start and stop signals from\n CPC G06T 1/20 (2013.01 ) ; G06F 9/5027\n the CPU and the simulation completion signal back to CPU ),\n GPU programs and input/output data are exchanged between\n ( 2013.01 ) ; G06T 1/60 ( 2013.01 ) ; CPU and the expansion card . Moreover, since on every time\n ( Continued ) step of the simulation the results from the previous time step\n( 58 ) Field of Classification Search are used but not changed, the results are preferably trans\n CPC ... GO6F 9/5027 ; G06F 2209/509 ; G06T 1/20 ; ferred back to CPU in parallel with the computation .\n GO6T 1/60 ; G06N 99/005 ; GO6N 37063\n See application file for complete search history . 56 Claims , 5 Drawing Sheets\n Expansion Cards 40\n\n 420\n ? e.com\n\n 403 435\n xxtes\n 19x VI 9XY\n SKM 2\n 450\n Swarum\n shokolaty\n bars CPU\n\n\n 19:43 Shader GPU .\n\n 180\n Outdoor\n yoles exi\n Teney bank\n 440\n 482 Now external\n texmex Tom FRAM\n UM\n WOX + vary but\n\n\n Wait for SWRP Svima i wait for swap\n otrputloutpan\n xure points\n ? output\n texture packs\n otinescioutput\n extere gointate\n plexulante\n 478\n ******** * herbimity\n Dank AM leration harasana\n\n\n en?\n 490\n Waxa ste\n tra\n axexkoren\n 499\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 3 of 22\n\n\n US RE48,438 E\n Page 2\n\n Related U.S. Application Data 2014/0032461 Al 1/2014 Weng\n 2014/0089232 A1 3/2014 Buibas et al .\n( 60 ) Provisional application No. 60 /826,892 , filed on Sep. 2014/0052679 Al\n 2015/0127149 Al\n 11/2014 Sinyavskiy et al .\n 5/2015 Sinyavskiy et al .\n 25 , 2006 . 2015/0134232 Al 5/2015 Robinson\n 2015/0224648 A1 8/2015 Lee et al .\n( 51 ) Int . Ci . 2016/0075017 A1 3/2016 Laurent et al.\n GOOT 1/20 ( 2006.01 ) 2016/0082597 A1 3/2016 Gorchetchnikov et al .\n GOON 37063 (2006.01 ) 2016/0096270 A1 4/2016 Gabardos et al .\n GOON 20/00 2016/0198000 Al 7/2016 Gorchetchnikov et al .\n ( 2019.01 ) 2017/0024877 A1 1/2017 Versace et al .\n( 52) U.S. Ci. 2017/0076194 A1 3/2017 Versace et al .\n CPC G06F 2209/509 (2013.01 ) ; GO6N 37063 2017/0193298 Al 7/2017 Versace et al .\n (2013.01 ) ; GOON 20/00 (2019.01 ) FOREIGN PATENT DOCUMENTS\n( 56) References Cited WO WO 2014/204615 12/2014\n U.S. PATENT DOCUMENTS WO WO 2015/143173 9/2015\n WO WO 2016/014137 1/2016\n 5,142,665 A * 8/1992 Bigus GOON 3/04\n 706/16 OTHER PUBLICATIONS\n 5,172,253 A 12/1992 Lynne\n 5,388,206 A 2/1995 Poulton et al . Montrym et al . , \u201c The GeForce 6800 \u201d , IEEE , 2005 , 11 pages. ( Year :\n 6,018,696 A 1/2000 Matsuoka et al . 2005) . *\n 6,336,051 B1 1/2002 Pangels et al. 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MIT Press , 1998 . * cited by examiner\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 7 of 22\n\n\nU.S. Patent Feb.i6, 2021 Sheet 1 of 5 US RE48,438 E\n\n\n\n\n 14? *\n\n\n\n\n 130\n ????????????\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 8 of 22\n\n\nU.S. Patent Feb. 16 , 2021 Sheet 2 of 5 US RE48,438 E\n\n\n\n\n I\n\n\n 220\n\n\n I\n\n\n\n\n RAM\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 9 of 22\n\n\nU.S. Patent Feb. 16 , 2021 Sheet 3 of 5 US RE48,438 E\n\n\n\n 13:25 326 330 FIG\n 3\n .\n 320\n\n\n ECXPANRSIDON CONTROLER INITIALIZATION\n 180\n EIXNTEPRUNATL TFEXRTUOREMS RTOEXATUMRE MBEAMNORKY POPULATION SBIHNADRIERS FRAMTO SMHEAMDOERRY BANK COMPUTATION )\n 4\n .\n (\n SEE\n FIG\n\n\n\n\n COMPUTATIONAL 3ST0RE3AM\n 309\n DATA\n 310\n PSDAHRASDTEAR GAENERADTOR\n 316\n BATA\n 314\n DATA\n 350\n\n 304\n IPANRPSUETR TEXTURE GENERATOR POPULATION COMPILER IPANRPSUETR TGENXETRAUTROER ODUATPUAT ACUMULATION INRAM\n 315\n\n 306 LAST T?ERATION YES\n 311 312\n\n 300\n UINTSERAECTIRON 3ST0RE2AM 307 GUINRTSAEPREFHAIRCE 305 SIMULATION INITIALIZATION PROGRES MONITOR RESULTS DISPLAY NO\n 390\n START GURSAPEHIRC INTERFACE INITIALIZATION INTERACTION USER\n 313\n END\n\n\n 308 317 318\n CPU120\n DOUATTPUAT 3ST0RE1AM\n O\n /\n I\n DISK\n\n\n INITIALIZATION DOUATPTUAT TODISK\n NO\n LAST I?TERATION YES\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 10 of 22\n\n\nU.S. Patent Feb. 16 , 2021 Sheet 4 of 5 US RE48,438 E\n\n\n Expansion Card 180\n\n\n\n Isoss foxxos ir\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 11 of 22\n\n\nU.S. Patent Feb. 16 , 2021 Sheet 5 of 5 US RE48,438 E\n\n\n\n\n Blsthepofdiwfc.amnicpxklotuniolndwahrstg 5\n .\n FIG\n\n\n\n\n 2\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 12 of 22\n\n\n US RE48,438 E\n 1 2\n GRAPHIC PROCESSOR BASED for input /output should be designed so that it provides the\n ACCELERATOR SYSTEM AND METHOD synchronization with computation .\n In the case of GPGPU , the computation itself is performed\n outside\nMatter enclosed in heavy brackets [ ] appears in the 5 \u201c peripheral of the CPU , so the complete system comprises three\noriginal patent but forms no part of this reissue specifica hardware, and\u201d components: user interactive hardware , disk\ntion ; matter printed in italics indicates the additions ing unit ( CPUcomputational\n ) establishes\n hardware. The central process\n communication and synchroni\nmade by reissue ; a claim printed with strikethrough zation between peripherals. Each of the peripherals is pref\nindicates that the claim was canceled, disclaimed, or held erably controlled by a dedicated thread that is executed in\ninvalid by a prior post- patent action or proceeding . 10 parallel with minimal interactions and dependencies on the\n other threads .\n RELATED APPLICATIONS A GPU on a conventional video card is usually controlled\n through OpenGL , DirectX , or similar graphic application\n The present application is a broadening reissue applica programming\ntion of U.S. Pat. No. 9,189,828, filed Jan. 3 , 2014, which 15 context of graphic interfaces (APIs ). Such APIs establish the\nclaims a priority benefit, under 35 U.S.C. $ 120 , as a con GPU are made . This operations, within which all calls to the\ntinuation of U.S. application Ser. No. 11 / 860,254 , now U.S. within the same threadcontext\n of\n only works when initialized\n execution that uses it . As a result,\nPat . No. 8,648,867 B2 , filed Sep. 24 , 2007 , entitled \u201c Graphic in a preferred embodiment, the context is initialized within\nProcessor Based Accelerator System and Method , \u201d which in\nturn claims the priority benefit, under 35 U.S.C. 8119 (e ) , of 20 aevercomputational thread. This creates complications , how\n , in the interaction between the user interface thread that\nU.S. Application No. 60/ 826,892 , filed Sep. 25 , 2006. Each\nof the above - identified applications is incorporated herein by changes parameters of simulations and the computational\nreference in its entirety. More than one reissue application thread that uses these parameters.\nhas been filed for the reissue of U.S. Pat. No. 9,189,828 , A solution as proposed here is an implementation of the\nincluding this application and a reissue continuation appli- 25 computational stream of execution in hardware, so that\ncation filed Dec. 29, 2020. thread and context initialization are replaced by hardware\n initialization . This hardware implementation includes an\n BACKGROUND expansion card comprising a printed circuit board having ( a )\n one or more graphics processing units , (b ) two or more\n Graphics Processing Units (GPUs) are found in video 30 associated memory banks that are logically or physically\nadapters ( graphic cards) of most personal computers ( PCs ) , partitioned, (c ) a specialized controller, and (d) a local bus\nvideo game consoles , workstations, etc. and are considered providing signal coupling compatible with the PCI industry\nhighly parallel processors dedicated to fast computation of standards ( this includes but is not limited to PCI -Express ,\ngraphical content. With the advances of the computer and PCI - X , USB 2.0 , or functionally similar technologies ). The\nconsole gaming industries, the need for efficient manipula- 35 controller handles most of the primitive operations needed to\ntion and display of 3D graphics has accelerated the devel- set up and control GPU computation . As a result, the CPU\nopment of GPUs . is freed from this function and is dedicated to other tasks . In\n In addition , manufacturers of GPUs have included general this case a few controls ( simulation start and stop signals\npurpose programmability into the GPU architecture leading from the CPU and the simulation completion signal back to\nto the increased popularity of using GPUs for highly paral- 40 CPU) , GPU programs and input/output data are the infor\nlelizable and computationally expensive algorithms outside mation exchanged between CPU and the expansion card .\nof the computer graphics domain . When implemented on Moreover, since on every time step of the simulation the\nconventional video card architectures, these general purpose results from the previous time step are used but not changed ,\nGPU ( GPGPU) applications are not able to achieve optimal the results are preferably transferred back to CPU in parallel\nperformance , however. There is overhead for graphics- 45 with the computation .\nrelated features and algorithms that are not necessary for In general, according to one aspect , the invention features\nthese non-video applications. a computer system . This system comprises a central pro\n cessing unit , main memory accessed by the central process\n SUMMARY ing unit , and a video system for driving a video monitor in\n 50 response to the central processing unit as is common . The\n Numerical simulations, e.g. , finite element analysis , of computer system further comprises an accelerator that uses\nlarge systems of similar elements ( e.g. neural networks, input data from and provides output data to the central\ngenetic algorithms, particle systems, mechanical systems) processing unit. This accelerator comprises at least one\nare one example of an application that can benefit from graphics processing unit, accelerator memory for the graphic\nGPGPU computation . During numerical simulations, disk 55 processing unit, and an accelerator controller that moves the\nand user input /output can be performed independently of input data into the at least one graphics processing unit and\ncomputation because these two processes require interac- the accelerator memory to generate the output data .\ntions with peripheral hardware ( disk , screen , keyboard , In the preferred , the central processing unit transfers the\nmouse , etc ) and put relatively low load on the central input data for a simulation to the accelerator, after which the\nprocessing unit/system (CPU) . Complete independence is 60 accelerator executes simulation computations to generate\nnot desirable , however; user input might affect how the the output data, which is transferred to the central processing\ncomputation is performed and even interrupt it if necessary. unit. Preferably, the accelerator controller dictates an order\nFurthermore, the user output and the disk output are depen- of execution of instructions to the at least one graphics\ndent on the results of the computation. A reasonable solution processing unit . The use of the separate controller enables\nwould be to separate input/output into threads, so that it is 65 data transfer during execution such that the accelerator\ninteracting with hardware occurs in parallel with the com- controller transfers output data from the accelerator memory\nputation . In this case whatever CPU processing is required to main memory of the central processing unit .\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 13 of 22\n\n\n US RE48,438 E\n 3 4\n In the preferred embodiment, the accelerator controller not limited to , workstations, server computers, supercom\ncomprises an interface controller that enables the accelerator puters, notebook computers, hand -held electronic devices\nto communicate over a bus of the computer system with the such as cell phones, mp3 players, or personal digital assis\ncentral processing unit. tants ( PDAs ) , multiprocessor systems, programmable con\n In general according to another aspect , the invention also 5 sumer electronics, networks of any of the above -mentioned\nfeatures an accelerator system for a computer system , which computing devices, and distributed computing environments\ncomprises at least one graphics processing unit , accelerator that including any of the above -mentioned computing\nmemory for the graphic processing unit and an accelerator devices.\ncontroller for moving data between the at least one graphics 10 In one implementation the GPU accelerator is imple\nprocessing unit and the accelerator memory .\n In general according to another aspect , the invention also mented as an expansion card 180 includes connections with\nfeatures a method for performing numerical simulations in a are installed along110with\n the motherboard , on which the one or more CPU's 120\n main , or system memory 130 and\ncomputer system . This method comprises a central process mass / non volatile data storage 140 , such as hard drive or\ning unit loading input data into an accelerator system from redundant array of independent drives (RAID ) array, for the\nmain memory of the central processing unit and an accel- 15 computer system 100. In the current example\nerator controller transferring the input data to a graphics card 180 communicates to the motherboard ,110 the expansion\nprocessing unit with instructions to be performed on the bus 190. This local bus 190 could be PCI , PCIviaExpress a local\ninput data . The accelerator controller then transfers output PCI - X , or any other functionally similar technology (de,\ndata generated by the graphic processing unit to the central 20 pending upon the availability on the motherboard 110 ) . An\nprocessing unit as output data .\n The above and other features of the invention including external version GPU accelerator is also a possible imple\nvarious novel details of construction and combinations of mentation . In this example, the external GPU accelerator is\nparts, and other advantages, will now be more particularly connected to the motherboard 110 through USB - 2.0 , IEEE\ndescribed with reference to the accompanying drawings and 1394 (Firewire ), or similar external /peripheral device inter\npointed out in the claims . It will be understood that the 25 face .\nparticular method and device embodying the invention are The CPU 120 and the system memory 130 on the moth\nshown by way of illustration and not as a limitation of the erboard 110 and the mass data storage system 140 are\ninvention . The principles and features of this invention may preferably independent of the expansion card 180 and only\nbe employed in various and numerous embodiments without communicate with each other and the expansion card 180\ndeparting from the scope of the invention . 30 through the system bus 200 located in the motherboard 110 .\n A system bus 200 in current generations of computers have\n BRIEF DESCRIPTION OF THE DRAWINGS bandwidths from 3.2 GB / s (Pentium 4 with AGTL + , Athlon\n XP with EVO ) to around 15 GB / s (Xeon Woodcrest with\n In the accompanying drawings, reference characters refer AGTL + , Athlon 64 /Opteron with Hypertransport), while the\nto the same parts throughout the different views. The draw- 35 local bus has maximal peak data transfer rates of 4 GB / s\nings are not necessarily to scale ; emphasis has instead been (PCI Express 16 ) or 2 GB / s ( PCI -X 2.0 ) . Thus the local bus\nplaced upon illustrating the principles of the invention . Of 190 becomes a bottleneck in the information exchange\nthe drawings: between the system bus 200 and the expansion card 180. The\n FIG . 1 is a schematic diagram illustrating a computer design of the expansion card and methods proposed herein\nsystem including the GPU accelerator according to an 40 minimizes the data transfer through the local bus 190 to\nembodiment of the present invention ; reduce the effect of this bottleneck .\n FIG . 2 is block diagram illustrating the architecture for the The system memory 130 is referred to as the main\nGPU accelerator according to an embodiment of the present random - access memory (RAM ) in the description herein .\ninvention; However, this is not intended to limit the system memory\n FIG . 3 is a block / flow diagram illustrating an exemplary 45 130 to only RAM technology. Other possible computer\nimplementation of the top level control of the GPU accel- storage media include , but are not limited to ROM ,\nerator system ; EEPROM , flash memory, or any other memory technology.\n FIG . 4 is a flow diagram illustrating an exemplary imple- In the illustrated example, the GPU accelerator system is\nmentation of the bottom level control of the GPU accelerator implemented on an expansion card 180 on which the one or\nsystem that is used to execute the target computation ; and 50 more GPU's 240 are mounted . It should be noted that the\n FIG . 5 is an example population of nine computational GPU accelerator system GPU 240 is separate from and\nelements arranged in a 3x3 square and a potential packing independent of any GPU on the standard video card 150 or\nscheme for texture pixels , according to an implementation of other video driving hardware such as integrated graphics\nthe present invention . systems. Thus the computations performed on the expansion\n 55 card 180 do not interfere with graphics display ( including\n DETAILED DESCRIPTION but not limited to manipulation and rendering of images ) .\n Various brand of GPU are relevant. Under current tech\n FIG . 1 shows a computer system 100 that has been nology, GPU's based on the GeForce series from NVIDIA\nconstructed according to the principles of the present inven- Corporation or the Catalyst series from ATI/ Advanced\ntion . 60 Micro Devices, Inc.\n In more detail, the computer system 100 in one example The output to a video monitor 170 is preferably through\nis a standard personal computer ( PC ) . However, this only the video card 150 and not the GPU accelerator system 180 .\nserves as an example environment as computing environ- The video card 150 is dedicated to the transfer of graphical\nment 100 does not necessarily depend on or require any information and connects to the motherboard 110 through a\ncombination of the components that are illustrated and 65 local bus 160 that is sometimes physically separate from the\ndescribed herein . In fact, there are many other suitable local bus 190 that connects the expansion card 180 to the\ncomputing environments for this invention, including, but motherboard 110 .\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 14 of 22\n\n\n US RE48,438 E\n 5 6\n FIG . 2 is a block diagram illustrating the general archi- not require hardware implementation. Also the partitioning\ntecture of the GPU accelerator system and specifically the scheme is also altered based on new designs or needs of the\nexpansion card 180 in which at least one GPU 240 and algorithms being employed. The reason for this partitioning\nassociated memories 210 and 250 are mounted . Electrical is further explained in the Data Organization section, below .\n( signal) and mechanical coupling with a local bus 190 5 A local bus interface 230 on the controller 220 serves as\nprovides signal coupling compatible with the PCI industry a driver that allows the controller 220 to communicate\nstandards ( this includes but is not limited to PCI , PCI -X , PCI through the local bus 190 with the system bus 200 and thus\nExpress, or functionally similar technology ). the CPU 120 and RAM 130. This local bus interface 230 is\n The GPU accelerator further preferably comprises one not intended to be limited to PCI related technology. Other\nspecifically designed accelerator controller 220. Depending 10 drivers can be used to interface with comparable technology\nupon the implementation , the accelerator controller 220 is as a local bus 190 .\nfield programmable gate array ( FPGA ) logic , or custom built Data Organization\napplication - specific (ASIC ) chip mounted in the expansion Each computational element discussed above has output\ncard 180 , and in mechanical and signal coupling with the variables that affect the rest of the system . For example in\nGPU 240 and the associated memories 210 and 250. During 15 the case of a neural network it is the output of a neuron . A\ninitial design , a controller can be partially or even fully computational element also usually has several internal\nimplemented in software, in one example. variables that are used to compute output variables , but are\n The controller 220 commands the storage and retrieval of not exposed to the rest of the system , not even to other\narrays of data ( on a conventional video card the arrays of elements of the same population, typically. Each of these\ndata are represented as textures, hence the term ' texture' in 20 variables is represented as a texture . The important differ\nthis document refers to a data array unless specified other- ence between output variables and internal variables is their\nwise and each element of the texture is a pixel of color access .\ninformation ), execution of GPU programs (on a conven- Output variables are usually accessed by any element in\ntional video card these programs are called shaders , hence the system during every time step . The value of the output\nthe term \u201c shader ' in this document refers to a GPU program 25 variable that is accessed by other elements of the system\nunless specified otherwise ), and data transfer between the corresponds to the value computed on the previous, not the\nsystem bus 200 and the expansion card 180 through the local current, time step . This is realized by dedicating two textures\nbus 190 which allows communication between the main to output variables \u2014 one holds the value computed during\nCPU 120 , RAM 130 , and disk 140 . the previous time step and is accessible to all computational\n Two memory banks 210 and 250 are mounted on the 30 elements during the current time step , another is not acces\nexpansion card 180. In some example, these memory banks sible to other elements and is used to accumulate new values\nseparated in the hardware, as shown, or alternatively imple- for the variable computed during the current time step .\nmented as a single , logically partitioned memory compo- In -between time steps these tw te res are switched , so\nnent. that newly accumulated values serve as accessible input\n The reason to separate the memory into two partitions 210 35 during the next time step , while the old input is replaced with\n250 stems from the nature of the computations to which the new values of the variable. This switch is implemented by\nGPU accelerator system is applied . The elements of com- swapping the address pointers to respective textures as\nputation ( computational elements ) are characterized by a described in the System and Framework section .\nsingle output variable . Such computational elements often Internal variables are computed and used within the same\ninclude one or more equations. Computational elements are 40 computational element. There is no chance of a race con\nsame or similar within a large population and are computed dition in which the value is used before it is computed or\nin parallel. An example of such a population is a layer of after it has already changed on the next time step because\nneurons in an artificial neural network (ANN ), where all within an element the processing is sequential. Therefore, it\nneurons are described by the same equation. As a result, is possible to render the new value of internal variable into\nsome data and most of the algorithms are common to all 45 the same texture where the old was read from in the texture\ncomputational elements within population , while most of the memory bank . Rendering to more than one texture from a\ndata and some algorithms are specific for each equation . single shader is not implemented in current GPU architec\nThus, one memory , the shader memory bank 210 , is used to tures, so computational elements that track internal variables\nstore the shaders needed for the execution of the required would have to have one shader per variable . These shaders\ncomputations and the parameters that are common for all 50 can be executed in order with internal variables computed\ncomputational elements and is coupled with the controller first, followed by output variables .\n220 only. The second memory, the texture memory bank Further savings of texture memory is achieved through\n250 , is used to store all the necessary data that are specific using multiple color components per pixel ( texture element)\nfor every computational element (including, but not limited to hold data . Textures can have up to four color components\nto , input data , output data , intermediate results, and param- 55 that are all processed in parallel on a GPU . Thus, to\neters ) and is coupled with both the controller 220 and the maximize the use of GPU architecture it is desirable to pack\nGPU 240 . the data in such a way that all four components are used by\n The texture memory bank 250 is preferably further par- the algorithm . Even though each computational element can\ntitioned into four sections . The first partition 250 a is have multiple variables, designating one texture pixel per\ndesigned to hold the external input data patterns. The second 60 element is ineffective because internal variables require one\npartition 250b is designed to hold the data textures repre- texture and output variables require two textures . Further\nsenting internal variables. The third partition 250c is more , different element types have different numbers of\ndesigned to hold the data textures used as input at a variables and unless this number is precisely a multiple of\nparticular computation step on the GPU 240. The fourth four, texture memory can be wasted .\npartition 250d holds the data textures used to accommodate 65 A more reasonable packing scheme would be to pack four\nthe output of a particular computational step on the GPU computational elements into a pixel and have separate\n240. This partitioning scheme can be done logically , does textures for every variable associated with each computa\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 15 of 22\n\n\n US RE48,438 E\n 7 8\ntional element. In this case the packing scheme is identical The crucial feature of the interaction between the User\nfor all textures, and therefore can be accessed using the same Interaction Stream 302 and the Computational Stream 303 is\nalgorithm . Several ways to approach this packing scheme the shift of priorities. Outside of the simulation , the system\nare outlined here. An example population of nine computa- 100 is driven by the user input, thus the User Interaction\ntional elements arranged in a 3x3 square (FIG . 5a ) can be 5 Stream 302 has the priority and controls the data exchange\npacked by element (FIG . 5b ) , by row (FIG . 5c ) , or by square 304 between streams. After the user starts the simulation , the\n( FIG . 5d) . Computational Stream 303 takes the priority and controls\n Packing by element ( FIG . 5b ) means that elements 1,2,3,4 the data exchange between streams until the simulation is\n finished or interrupted 350 .\ngo into first pixel ; 5,6,7,8 go into second pixel ; 9 goes into\nthird pixel . This is the most compact scheme , but not 10 an The user starts 300 the framework through the means of\nconvenient because the geometrical relationship is not pre theoperating system and interacts with the software through\nserved during packing and its extraction depends on the size 306user interaction section 305 of the graphic user interface\n executed on the CPU 120. The start 300 of the imple\nof the population .\n Packing by row ( column; FIG . 5c ) means that elements 15 initializationbegins\n mentation with a user action that causes a GUI\n 307 , Disk input /output initialization 308 on the\n1,2,3 go into pixel ( 1,1 ) ; 3,4,5 go into pixel (2,1 ) , 7,8,9 go CPU 120 , and controller initialization 320 of the GPU\ninto pixel ( 3,1 ) . With this scheme the element\u2019s y coordinate accelerator on the expansion card 180. GUI initialization\nin the population is the pixel's y coordinate, while the includes opening of the main application window and setting\nelement\u2019s x coordinate in the population is the pixel's x the interface tools that allow the user to control the frame\ncoordinate times four plus the index of color component. 20 work . Disk I/O initialization can be performed at the start of\nFive by five populations in this case will use 2x5 texture, or the framework , or at the start of each individual simulation .\n10 pixels . Five of these pixels will only use one out of four The user interaction 305 controls the setting and editing of\ncomponents , so it wastes 37.5 % of this texture. 25x1 popu- the computational elements, parameters, and sources of\nlation will use 6x1 texture ( six pixels ) and will waste 12.5 % external inputs. It specifies which equations should have\nof it . 25 their output saved to disk and / or displayed on the screen . It\n Packing by square ( FIG . 5d ) means that elements 1,2,4,5 allows the user to start and stop the simulation . And it\ngo into pixel ( 1,1 ) ; 3,6 go into pixel ( 1,2 ) ; 7,8 go into pixel performs standard interface functions such as file loading\n( 2,1 ) , and 9 goes into pixel (2,2 ) . Both the row and the and saving , interactive help , general preferences and others.\ncolumn of the element are determined from the row (col- The user interaction 305 directs the CPU 120 to acquire\numn ) of the pixel times two plus the second ( first) bit of the 30 the new external input textures needed (this includes but is\ncolor component index . Five by five populations in this case not limited to loading from disk 140 or receiving them in\nwill use 3x3 texture , or 9 pixels . Four of these pixels will real time from a recording device ), parses them if necessary\nonly use out of four components, and one will only use 309 , and initializes their transfer the expansion card 180 ,\none component, so it wastes 34.4 % of this texture . This is where they are stored 325 in the texture memory bank 250\nmore advantageous than packing by row , since the texture is 35 by the controller 220. The user interaction 305 also directs\nsmaller and the waste is also lower. 25x1 population on the the CPU 120 to parse populations of elements that will be\nother hand will use 13x1 texture ( thirteen pixels ) and waste used in the simulation, convert them to GPU programs\n> 50 % of it , which is much worse than packing by row . ( shaders ) , compile them 310 , and initializes their transfer to\n In order to eliminate waste altogether the population the expansion card 180 , where they are stored 326 in the\nshould have even dimensions in the square packing, and it 40 shader memory bank 210 by the controller 220. This opera\nshould have a number of columns divisible by four in row tion is accompanied by the upload 309 of the initial data into\npacking. Theoretically, the chances are approximately the input partition of the texture memory bank 250 , and\nequivalent for both of these cases to occur, so the particular stores the shader order of execution in the controller 220 .\ntask and data sizes should determine which packing scheme The user can perform operations 309 and 310 as many times\nis preferable in each individual case . 45 as necessary prior to starting the simulation or between\n The System and Framework simulations .\n FIG . 3 shows an exemplary implementation of the top The editing of the system between simulations is difficult\nlevel system and method that is used to control the compu- to accomplish without the hardware implementation of the\ntation . It is a representation of one of several ways in which computational thread suggested herein . The system of equa\na system and method for processing numerical techniques 50 tions ( computational elements) is represented by textures\ncan be implemented in the invention described herein and so that track variables plus shaders that define processing\nthe implementation is not intended to be limited to the algorithms. As mentioned above , textures, shaders and other\nfollowing description and accompanying figure . graphics related constructs can only be initialized within the\n The method presented herein includes two execution rendering context, which is thread specific . Therefore tex\nstreams that run on the CPU 120 - User Interaction Stream 55 tures and shaders can only be initialized in the computa\n302 and Data Output Stream 301. These two streams pref- tional thread .\nerably do not interact directly, but depend on the same data Network editing is a user - interactive process, which\naccumulated during simulations . They can be implemented according to the scheme suggested above happens in the\nas separate threads with shared memory access and executed User Interaction Stream 302. The simulation software thus\non different CPUs in the case of multi -CPU computing 60 has to take the new parameters from the User Interaction\nenvironment. The third execution stream \u2014 Computational Stream 302 , communicate them to the Computational\nStream 303 runs on the GPU accelerator of the expansion Stream 303 and regenerate the necessary shaders and tex\ncard 180 and interacts with the User Interaction Stream 302 tures . This is hard to accomplish without a hardware imple\nthrough initialization routines and data exchange in between mentation of the Computational Stream 303. The Compu\nsimulations. The Computational Stream 303 interacts with 65 tational Stream 303 is forked from the User Interaction\nthe User Interaction Stream and the Data Output Stream Stream and it can access the memory of the parent thread,\nthrough synchronization procedures during simulations. but the reverse communication is harder to achieve. The\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 16 of 22\n\n\n US RE48,438 E\n 9 10\ncontroller 220 allows operations 309 and 310 to be per- timestep ( ) , TSimulator::outfileInterval ( ), and TSimulator::\nformed as many times as necessary by providing the nec- outmode ( ) , the application can set the time step of the\nessary communication to the User Interaction Stream 302 . simulation , the time step of disk output, and the mode of the\n After execution of the input parser texture generation 309 5 disk output. The external input pattern should be packed into\nand population parser shader generator and compiler 310 are a TPattern object and bound to the simulation object through\nperformed at least once , the user has the option to initialize TSimulator:: resetInputs( ) . method . TSimulator::\nthe simulation 311. During this initialization the main con simLength ( ) sets the length of the simulation .\ntrol of the framework is transferred to the GPU accelerator The second step is to create at least one population of\nsystem's accelerator controller 220 and computation 330 is equations ( Tpopulation object ). Population holds one equa\nstarted\ninterrupt(see\n the FIG . 4; 420, change\n simulation ). The the\n userinput\n retains\n , or the abilitythe\n to change to 10 tion object TEquation. This object contains only a formula\ndisplay properties of the framework , but these interactions the and does not hold element- specific data , so all elements of\nare queued to be performed at times determined by the population can share single TEquation .\ncontroller - driven data exchange 314 and 316 to avoid the before execution The TEquation object is converted to a GPU program\ncorruption of the data . 15 . GPU programs have to be executed within\n The progress monitor 312 is not necessary for perfor creates this context , within\n a graphical context which is stream specific . TSimulator\nmance , but adds convenience. It displays the percentage of fore all programs and dataa arrays Computational Stream , there\ncompleted time steps of the simulation and allows the user computation have to be initialized that within\n are necessary for\n Computational\nto plan the schedule using the estimates of the simulation Stream . Constructor of TPopulation is called from User\nwall clock times . Controller - driven data exchange 314 20 Interaction\nupdates the display of the results 313. Online screen output tialized in this constructor .\n Stream , so no GPU - related objects can be ini\nfor the user selected population allows the user to monitor\nthe activity and evaluate the qualitative behavior of the to TPopulation overcome\n :: fillElements ( ) is a virtual method designed\n this difficulty. It is called from within the\nnetwork . Simulations with unsatisfactory behavior can be Computational Stream after TSimulator ::user\n networkCreate ( ) is\nterminated early to change parameters and restart . Control- 25 called in the User Interaction Stream\nler - driven data exchange 314 also drives the output of the TPopulation :: fillElements ( ) to create TEquation and other\n . A has to override\nresults to disk 317. Data output to disk for convenience can computation related objects both element independent and\nbe done on an element per file basis . A suggested file format element-specific. Element independent objects include sub\nincludes a leftmost column that displays a simulated time for\neach of the simulation steps and subsequent columns that 30 components of TEquation and\n handle interdependencies objectsvariables\n between that describe how to\n implemented\ndisplay variable values during this time step in all elements through derivatives of TGate class .\nwith identical equations (e.g. all neurons in a layer of a Element - specific data is held in TElement objects. These\nneural network ).\n Controller -driven data exchange or input parser texture objects. Therereferences\n objects hold to TEquation and a set of TGate\n is one TElement per population, but the size\ngenerator 316 allows the user to change input that is gen- 35 of data arrays within this object corresponds to population\nerated on the fly during the simulation . This allows the size . All TElement objects have to be added to the TSimu\nframework monitoring of the input that is coming from a lator list of elements by calling TSimulator:: addUnit ( )\nrecording device ( video camera, microphone, cell recording method from TPopulation :: fillElements ( ).\nelectrode, etc ) in real time . Similar to the initial input parser Finally, TPopulation :: fillElements ( ) should contain a set\n309\ndata, itarray\n preprocesses\n suitable the\n for input\n textureintogeneration\n a universaland\n format of the 40 of TElement:: add* Dependency ( ) calls for each element.\n generates\ntextures . Unlike the initial parser 309 , here the textures are every Each of these calls sets a corresponding dependency for\ntransferred to hardware not whenever ready but upon the pendentTGatepart object. Here TGate object holds element inde\n of dependency and TElement::\nrequest of the controller 220 . add * Dependency sets element-specific details.\n The controller 220 also drives the conditional testing 315 45 System provided TPopulation handles the output of com\nand 318 informs the CPU - bound streams whether the simu putational elements, both when they need to exchange the\nlation is finished . If so , the control returns to the User data and when they need to output it to disk . User imple\nInteraction Stream . The user then can change parameters or\ninputs ( 309 and 310 ) , restart the simulation (311 ) or quit the mentation of TPopulation derivative can add screen output.\n Listing 1 is an example code of the user program that uses\nframework (390 ) . 50\n a recurrent competitive field (RCF ) equation:\n SANNDRA ( Synchronous Artificial Neuronal Network\nDistributed Runtime Algorithm ; http://www.kinness.net/\nDocs /SANNDRA /html) was developed to accelerate and Listing 1\noptimize processing of numerical integration of large non\nhomogenous systems of differential equations. This library 55 uint16_t static floatw m_compet\n = 3 , h = 3 ; = 0.5 ;\nis fully reworked in its version 2.x.x to support multiple static float m_persist = 1.0 ;\ncomputational backends including those based on multicore class TCablePopRCF : public TPopulation\nCPUs , GPUs and other processing systems . GPU based {TEq_RCF * m_equation ;\nbackend for SANNDRA -2.x.x can serve as an example TGate * m_gatel;\npractical software implementation of the method and archi- 60 TGate * m_gate2;\ntecture described above and pictorially represented in FIG . void createGatingStructure( )\n3. {\n To use SANNDRA, the application should create a m_gate2 m_gatel = new TGate ( 0 );\nTSimulator object either directly or through inheritance . } ; = new TGate ( 1 ) ;\nThis object will handle global simulation properties and 65 void createUnitStructure ( TBasicUnit* u )\ncontrol the User Interaction Stream , Data Output Stream , {\nand Computational Stream . Through TSimulator ::\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 17 of 22\n\n\n US RE48,438 E\n 11 12\n -continued expensive operation , computationally, but since the textures\n are referred to by texture IDs ( pointers ), swapping these\n Listing 1 pointers for input and output textures after each time step\nu-> addO20PInputDependency (m_gatel, O. , 0. , 0.004 , 0. , 0 , 0 ) ; achieves the same result at a much lesser cost .\n 5\nu- > addFullDependency (m_gate2, population ( ) ); In the hardware solution suggested herein , ID swapping is\n} equivalent to swapping the base memory address for two\npublic : TCablePopRCF ( ) : TPopulation ( \" compCPU RCF \u201d , w , h , true) { } ;\n-TCablePopRCFO ) { if (m_equation ) delete m_equation ; partitions of the texture memory bank 250. They are\n if (m_gatel) delete m_gatel;\n if (m_gate2) delete m_gate2 ; } ;\n swapped 485 during synchronization ( 485 , 430 , and 455 ) so\nbool fillElements( TSimulator * sim ) ; 10 that data transfer 445 and the computation 435-487 proceeds\n}; immediately and in parallel with data transfer as shown in\nbool TCablePopRCF :: fillElements ( TSimulatior* sim) FIG . 4. A hardware solution allows this parallelism through\n{ access of the controller 220 to the onboard texture memory\nm_equation = new TEQ_RCF (this, m_compet, m_persist );\ncreateGatingStructure ( ) ; bank 250 .\nfor( size_t i = 0 ; i < xSize ( ) ; ++ i ) 15\n The main computation and data exchange are executed by\n for(size_t j = 0 ; j < ySize ( ) ; ++ i)\n{ the controller 220. It runs three parallel substreams of\nTElement * u = new TCPUElement(this , m_equation, i , j ) ; execution : Computational Substream 403 , Data Output Sub\nsim-> addUnit( u ); stream 402 , and Data Input Substream 404. These streams\ncreateUnitStructure ( u );\n} 20 are synchronized with each other during the swap of pointers\nReturn true ; 485 to the input and output texture memory partitions of the\n} texture memory bank 250 and the check for the last iteration\nint\nmain ( ) 487. Algorithmically, these two operations are a single\n{ atomic operation, but the block diagram shows them as two\n// Input pattern generation ( 309 in FIG.3 ) 25 separate blocks for clarity.\nuint32_t * pat = new uint32_t [ w * h ];\nTRandom < float > randGen (0 ) ; The Computational Substream 403 performs a computa\nfor (uint32_t I = 0 ; I < w * h ; ++ i )\npat [i] = randGen.random ( ) ; tional cycle including a sequential execution of all shaders\nTpattern * p = new Tpattern (pat, w, h ) ; that were stored in the shader memory bank 210 using the\n// Setting up the simulation\n 30\n appropriate input and output textures. To begin the simula\nTSimulator * cableSim = new TSimulator ( \"data \" ) ; // ( 308 and 320 in tion the controller 220 initializes three execution substreams\nFIG. 3)\ncableSim- >timestep ( 0.05 ) ; // (320 in FIG . 3 ) 403 , 402 , and 404. On every simulation step , the Compu\ncableSim-> resetInputs (p ); // (325 in FIG . 3 ) tational Substream 403 determines which textures the GPU\ncableSim- > outfileInterval(0.1 ); // (308 in FIG . 3 ) 240 will need to perform the computations and initiates the\ncableSim- > outmode (SANNDRA ::timefunc ); // ( 308 in FIG . 3 )\ncableSim- > simLength (60.0 ); // (320 in FIG . 3 ) 35 upload 435 of them onto the GPU 240. The GPU 240 can\n// Preparing the population communicate directly with the texture memory bank 250 to\nTPopulation * cablePop new TCablePopRCFO ); // (310 in FIG . 3 ) upload the appropriate texture to perform the computations .\ncableSim- > networkCreate ( ); // (326 in FIG . 3 ) The controller 220 also pulls the first shader (known by the\nuint16_t user = 1 ;\nwhile (user) stored order ) from the shader memory bank 210 and uploads\n{ 40 450 it onto the GPU 240 .\nif (! cableSim-> simulationStart ( true, 1 ) ) // ( 311 in FIG . 3 )\nexit ( 1 ) ; The GPU 240 executes the following operations in this\nstd ::cout << \" Repeat ? \\ n \" ; // (305 in FIG . 3 )\nstd :: cin >> user; // ( 305 in FIG . 3 )\n order : performs the computation ( execution of the shader )\nif (user 1 ) 470 ; tells the controller 220 that it is done with the compu\ncableSim- > networkReset ( ); // ( 305 in FIG . 3 ) tations for the current shader; and after all shaders for this\n 45 particular equation are executed sends 480 the output tex\n{\nIf (cableSim ) tures to the output portion of the texture memory bank 250 .\nDelete cableSim ; // Also deletes cablePop and its internals This cycle continues through all of the equations based on\nexit (0 ) ;\n}; the branching step 482 .\n 50 An example shader that performs fourth order Runge\n FIG . 4 is a detailed flow diagram illustrating a part of an Kutta numerical integration is shown in Listing 2 using\nexemplary implementation of the bottom level system and GLSL notation ;\nmethod performed during the computation on the GPU\naccelerator of the expansion card 180 and is a more detailed Listing 2\nview of the computational box 330 in FIG . 3. FIG . 4 is a 55\nrepresentation of one of several ways in which a system and uniform sampler2DRect Variable ;\nmethod for processing numerical techniques can be imple uniform float integration_step ;\n float halfstep = integration_step * 0.5 ;\nmented .\n With systems of equations that have complex interdepen float fl_6step = integration_step / 6.0 ;\n vec4 output = texture2DRect (Variable, gl_TexCoord [0 ] .st );\ndencies it is likely that the variable in some equation from 60 // define equation here\na previous time step has to be used by some other equation vec4 rungekutta4 ( vec4 x )\nafter the new values of this variable are already computed {\n const vec4 kl = equation ( x );\nfor new time step . To avoid data confusion , the new values const vec4 k2 equation ( x + halfstep * kl ) ;\nof variables should be rendered in a separate texture. After const vec4 k3 equation ( x + halfstep * k2 );\nthe time step is completed for all equations, these new values 65 const vec4 k4 = equation ( x + integration step * k3 ) ;\nshould be copied over old values so that they are used as return fl_6step * (kl + 2.0 * (k2 + k3 ) + k4 );\ninput during the next time step . Copying textures is an\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 18 of 22\n\n\n US RE48,438 E\n 13 14\n -continued CONCLUSION\n Listing 2 This GPU accelerator system offers the following poten\n }\n tial advantages:\n Void main (void ) 5 1. Limited computations on the CPU 120. The CPU 120\n { is only used for user input, sending information to the\n output + = rungekutta4 (output );\n gl_FragColor = output;\n controller 220 , receiving output after each computational\n } cycle ( or less frequently as defined by the user ), writing this\n output to disk 140 , and displaying this output on the monitor\n 10 170. This frees the CPU 120 to execute other applications\n The shader in Listing 2 can be executed on conventional and allows the expansion card to run at its full capacity\nvideo card . Using the controller 220 this code can be further without being slowed down by extensive interactions with\noptimized , however. Since the integration step does not the CPU 120 .\nchange during the simulation , the step itself as well as the 2. Minimizing data transfer between the expansion card\nhalfstep and % of the step can be computed once per 15 180 and the system bus 200. All of the information needed\nsimulation , and updated in all shaders by a shader update to perform the simulations will be stored on the expansion\nprocedures 310 , 326 discussed above . card 180 and all simulations will take place on it . Further\n After all of the equations in the computational cycle are more , whatever data transfer remains necessary will take\ncomputed the main execution substream 403 on the control place in parallel with the computation , thus reducing the\nler 220 can switch 485 the reference pointers of the input and 20 impact\n 3. New of this\n waytransfer on the\n to execute GPUperformance\n programs (. shaders ). Previ\noutput portions of the texture memory bank 250 . ously, the CPU 120 had full control over the order of\n The two other substreams of execution on the controller shader's execution and was required to produce specific\n220 are waiting ( blocks 430 and 455 , respectively) for this commands on every cycle to tell the GPU 240 which shader\nswitch to begin their execution . The Data Input Substream 25 to use . With the invention disclosed herein , shaders will\n404 is controlling 440 the input of additional data from the initially be stored on the shader memory bank 210 on the\nCPU 120. This is necessary in cases where the simulation is expansion card 180 and will be sent to the GPU 240 for\nmonitoring the changing input, for example input from a execution by the general purpose controller 220 located on\nvideo camera or other recording device in the real time . This the expansion card .\nsubstream uploads new external input from the CPU 120 to 30 4. Multiple parallelisms . The GPU 240 is inherently\nthe texture memory bank 250 so it can be used by the main parallel and is well suited to perform parallel computations.\ncomputational substream 403 on the next computational step In parallel with the GPU 240 performing the next calcula\nand waits for the next iteration 475. The Data Output tion , the controller 220 is uploading the data from the\nSubstream 445 controls the output of simulation results to previous calculation into main memory 130. Furthermore,\nthe CPU 120 if requested by the user . This substream 35 the CPU 120 at the same time uses uploaded previous results\nuploads the results of the previous step to the main RAM to save them onto disk 140 and to display them on the screen\n130 so that the CPU 120 can save them on disk 140 or show through the system bus 200 .\nthem on the results display 313 and waits for the next 5. Reuse of existing and affordable technology. All hard\niteration 460 . ware used in the invention and mentioned here - in are based\n Since the Computational Substream 403 determines the 40 on currently available and reliable components. Further\ntiming of input 440 and output 445 data transfers, these data advance of these components will provide straightforward\ntransfers are driven by the controller 220. To further reduce improvements of the invention .\nthe data transfer overhead ( and disk 140 overhead also ) the While this invention has been particularly shown and\ncontroller 220 initiates transfer only after selected compu- described with references to preferred embodiments thereof,\ntational steps . For example, if the experimental data that is 45 it will be understood by those skilled in the art that various\nsimulated was recorded every 10 milliseconds (msec ) and changes in form and details may be made therein without\nthe simulation for better precision was computed every 1 departing from the scope of the invention encompassed by\nmsec , then only every tenth result has to be transferred to the appended claims .\nmatch the experimental frequency.\n This solution stores two copies of output data , one in the 50 What is claimed is :\nexpansion card texture memory bank 250 and another in the 1. \u00c0 computer system , comprising:\nsystem RAM 130. The copy in the system RAM 130 is a central processing unit to receive input data ;\naccessed twice : for disk I/O and screen visualization 313. An main memory , operably coupled to the central processing\nalternative solution would be to provide CPU 120 with a unit via a bus , to store the input data received by the\ndirect read access to the onboard texture memory bank 250 55 central processing unit;\nby mapping the memory of the hardware onto a global an accelerator, operably coupled to the central processing\nmemory space . The alternative solution will double the unit and the [first] main memory via the bus , to receive\ncommunication through the local bus 190. Since the goal at least a portion of the input data from the main\ndiscussed herein is reducing the information transfer through memory , the accelerator comprising:\nthe local bus 190 , the former solution is favored . 60 at least one graphics processing unit to perform a\n The main substream 403 determines if this is the last sequence of computations on the at least a portion of\niteration 487. If it is the last iteration , the controller 220 the input data so as to generate output data , the\nwaits for the all of the execution substreams to finish 490 sequence of computations representing an artificial\nand then returns the control to the CPU 120 , otherwise it neural network, intermediate computations in the\nbegins the next computational cycle . 65 sequence of computations representing respective\n This repeats through all of the computational cycles of the layers of the artificial neural network and yielding\nsimulation . intermediate results; and\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 19 of 22\n\n\n US RE48,438 E\n 15 16\n accelerator memory , operably coupled to the [ graphic ] system comprising a central processing unit (CPU) , a main\n at least one graphics processing unit, to store the memory operably coupled to the central processing unit via\n results of the [ plurality of sequential] sequence of a bus , an accelerator operably coupled to the CPU and the\n computations; and main memory via the bus , the accelerator comprising a\n a controller, operably coupled to the at least one graphics 5 graphics processing unit (GPU) and an accelerator memory,\n processing unit and the accelerator memory, to initial- the method comprising:\n ize textures and shaders in the accelerator memory for ( A ) performing, by the GPU , the sequence of computa\n performing the sequence of computations, to control tions on a first portion of [ the] input data so as to\n performance of the sequence of computations by the at generate a first portion of [the] output data , the first\n least one graphics processing unit, to transfer the at 10 portion of the output data representing an output of a\n least a portion of the input data into the accelerator neuron in a first layer of the artificial neural network,\n memory during performance of the intermediate com intermediate computations in the sequence of compu\n putations in the sequence of computations by the at tations yielding intermediate results , wherein perform\n least one graphics processing unit, and to transfer at ing the sequence of computations on the first portion of\n least a portion of the output data from the accelerator 15 the input data comprises ( i ) assigning an output vari\n memory to the main memory during performance of the\n intermediate computations in the sequence of compu able to a first texture and a second texture , the output\n tations by the at least one [ graphic ] graphics processing variable being included in a first computational ele\n unit . ment of a plurality of computational elements, the\n 2. The computer system of claim 1 , wherein the central 20 plurality of computational elements representing the\nprocessing unit is configured to receive the input data in sequence of computations and ( ii ) accumulating a first\nresponse to a user interaction . value for the output variable in the first texture during\n 3. The computer system of claim 1 , wherein : a first time step ;\n the central processing unit is configured to receive the ( B ) in parallel with performing the sequence of compu\n input data at a first rate ; and 25 tations by the GPU in ( A ), transferring a second portion\n the at least one graphics processing unit is configured to of the input data from the main memory to the accel\n perform the sequence of computations at a second rate erator via the bus ; [ and]\n different than the first rate . ( C ) in parallel with performing the sequence of compu\n 4. The computer system of claim 1 , wherein the main tations by the GPU in ( A ), transferring a second portion\nmemory is configured to store a copy of the output data 30 of the output data from the accelerator memory to the\nstored in the accelerator memory . main memory via the bus, the second portion of the\n 5. The computer system of claim 1 , wherein an output of output data representing an output of a neuron in a\nat least one computation in the sequence of computations second layer in the artificial neural network ; and\nrepresents an output of at least one neuron in an artificial ( D ) performing, by the GPU , the sequence of computa\nneural network . 35 tions on the second portion of the input data , wherein\n 6. The computer system of claim 1 , wherein accelerator performing the sequence of computationson the second\nmemory comprises: portion of the input data comprises ( i ) accumulating a\n a first memory bank to store parameters common to all of second value for the output variable in the second\n the computations in the sequence of computations; and texture during a second time step and ( ii) making the\n a second memory bank to store data specific to at least one 40 first value of the output variable in the first texture\n computation in the sequence of computations. accessible to other computational elements in the plu\n 7. The computer system of claim 1 , wherein the controller rality of computational elements during the second\nis configured to transfer the output data from the accelerator time step.\nmemory to the main memory without transferring any of the 13. The method of claim 12 , further comprising:\nintermediate results from the accelerator memory to the 45 storing the input data in the main memory in response to\nmain memory so as to reduce data transfer via the bus . a user interaction .\n 8. The computer system of claim 1 , wherein the controller 14. The method of claim 12 , further comprising:\nis configured to transfer at least a portion of the output data receiving the input data at a first rate; and\nfrom the accelerator memory to the main memory after the wherein ( A ) comprises performing the sequence of com\nat least one graphics processing unit has begun to perform 50 putations at a second rate different than the first rate .\nanother sequence of computations. [ 15. The method of claim 12 , wherein ( A ) comprises:\n 9. The computer system of claim 8 , wherein the controller generating an output representative of an output of at least\nis configured to initiate transfer of the at least a portion of the one neuron in an artificial neural network .]\ninput data and to transfer the at least a portion of the output 16. The method of claim 12 , wherein (C ) comprises:\ndata in parallel with performance of at least one computation 55 transferring the second portion of the output data from the\nin the other sequence of computations by the at least one accelerator memory to the main memory without trans\ngraphics processing unit . ferring any of the intermediate results of the plurality of\n 10. The computer system of claim 1 , wherein the con sequential computations from the accelerator memory\ntroller is configured to control execution of the sequence of to the main memory so as to reduce data transfer via the\ncomputations by the at least one graphics processing unit . 60 bus .\n 11. The computer system of claim 1 , further comprising: 17. The method of claim 12 , wherein ( C ) comprises :\n at least one of a video camera, a microphone, or a cell transferring the second portion of the output data from the\n recording electrode, operably coupled to the central accelerator memory to the main memory after the GPU\n [ processor) processing unit , to acquire the input data in has begun to perform another sequence of computa\n real time . 65 tions.\n 12. A method of performing a sequence of computations 18. The method of claim 17 , wherein (C ) further com\nrepresenting an artificial neural network on a computer prises:\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 20 of 22\n\n\n US RE48,438 E\n 17 18\n initiating transfer of the second portion of the output data 27. The method of claim 26 , further comprising :\n in parallel with performance of at least one computa- storing, in a second memory partition of the memory, data\n tion in the other sequence of computations. specific to the first computation in the sequence of\n 19. The method of claim 12 , further comprising : computations.\n acquiring the input data in real time with at least one of 5 28. The method of claim 27, further comprising :\n a video camera , a microphone, or a cell recording storing, in the second memory partition , external input\n electrode operably coupled to the CPU . data patterns, representations of internal variables, an\n 20. The method of claim 12 , further comprising : input of the computation in the sequence of computa\n storing parameters common to all of the computations in 10 tions , and the output of the computation in the sequence\n the sequence of computations in a first memory bank in of computations.\n the accelerator memory ; and 29. The method of claim 21 , wherein storing the first\n storing data specific to at least one computation in the output data comprises :\n sequence of computations in a second memory bank in accumulating, in the memory, outputs of computational\n the accelerator memory. 15 elements executed by the GPU in performing the first\n 21. A method of performing a sequence of computations computation in the sequence of computations.\nrepresenting an artificial neural network, the method com- 30. The method of claim 21 , further comprising:\nprising : storing, in the memory, an output of a previous compu\n receiving, at a central processing unit ( CPU ), first input tation in the sequence of computations; and\n data acquired from an external system in real time; 20 accessing, by the GPU , the output of the previous com\n initializing, by a controller operably coupled to a graph- putation during performance of the computation in the\n ics processing unit (GPU ), textures and shaders in a sequence of computations.\n memory opera coupled to the GPU ; 31. The method of claim 21 , wherein performing the first\n transferring the first input data received by the CPU to the computation comprises executing a plurality of computa\n memory operably coupled to the GPU : 25 tional elements representing a layer of neurons in an arti\n performing, by the graphics processing unit (GPU ), a first ficial neural network.\n computation in the sequence of computations on the 32. The method of claim 31 , wherein all neurons in the\n first input data based on the textures and shaders to layer of neurons are described by the same equation .\n generate first output data , computations in the 30 33. The method of claim 21 , further comprising :\n acquiring the second input data with at least one of a\n sequence of computations representing respective lay\n ers of neurons in the artificial neural network , an video camera , a microphone, or a cell recording elec\n trode .\n output of the first computation in the sequence of 34. The method of claim 21 , further comprising :\n computations representing an output of a first neuron in loading the second input data from disk .\n a first layer in the artificial neural network ; 35 35. A system for performing a sequence of computations,\n storing , in the memory operably coupled to the GPU , the the system comprising:\n first input data and the first output data ; and a camera to generate input data in real time ;\n transferring second input data acquired from the external a first memory partition ;\n system in real time into the memory operably coupled a second memory partition operably coupled to the first\n to the GPU after the GPU starts the first computation 40 memory partition ; and\n and before the GPU starts a second computation of the a processing unit , operably coupled to the camera , the\n sequence of computations, an output of the second first memory partition , and the second memory parti\n computation in the sequence of computations repre tion , to perform the sequence of computations on a first\n senting an output of a second neuron in a second layer portion of the input data so as to generate a first\n in the artificial neural network . 45 portion of output data , intermediate computations in\n 22. The method of claim 21 , wherein transferring the the sequence of computations yielding intermediate\nsecond input data comprises transferring the second input results, the first portion of the output data representing\ndata via a bus operably coupled to the CPU . an output of an artificial neural network,\n 23. The method of claim 21 , further comprising: wherein the first memory partition is configured to trans\n transferring the first output data from the memory to 50 fer a second portion of the input data to the second\n another memory during the second computation in the memory partition in parallel with performance the\n sequence of computations. sequence of computations by the processing unit ,\n 24. The method of claim 23, further comprising: wherein the second memory partition is configured to\n storing intermediate results of the sequence of computa 55 transfer a second portion of the output data to the first\n tions in the memory, and memory partition in parallel with performance the\n wherein transferring the first output data from the sequence of computations by the processing unit, and\n wherein the sequence of computations represents the\n memory to the other memory occurs without transfer artificial neural network , each neuron in the artificial\n ring the intermediate results of the sequence of com neural network has an output variable assigned to a\n putations. 60 first texture and a second texture in the memory , the first\n 25. The method of claim 23 , wherein transferring the texture holds a first value of the output variable com\nsecond input data and transferring the first output data puted during a previous time step of the sequence of\noccurs in parallel . computations and accessible to other neurons in the\n 26. The method of claim 21 ,further comprising: neural network during a current time step of the\n storing , in a first memory partition of the memory, param- 65 sequence of computations and the second texture accu\n eters common to all of the computations in the mulates a second value of the output variable computed\n sequence of computations. during the current time step .\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 21 of 22\n\n\n US RE48,438 E\n 19 20\n 36. The system of claim 35, wherein the first memory in the sequence of computations representing layers\npartition and the second memory partition are logical par of the neural network and yielding intermediate\ntitions . results ; and\n 37. The system of claim 35, wherein the processing unit is accelerator memory, operably coupled to the at least\ncomprises a graphics processing unit ( GPU ) . 5\n one processing unit, to store the results of the\n 38. The system of claim 35, wherein the processing unit is sequence of computations; and\nconfigured to receive the input data at a first rate and to a controller, operably coupled to the at least one\nperform the sequence of computations at a second rate is processing unit and the accelerator memory, to con\ndifferent than the first rate. trol transfer of the at least a portion of the input data\n 39. The system of claim 35, wherein the second memory 10 into the accelerator memory during performance of\npartition is configured to transfer the second portion of the the intermediate computations in the sequence of\noutput data to the first memory partition without transfer computations by the at least one processing unit, to\nring any of the intermediate results to the first memory control transfer at least a portion of the output data\npartition .\n 40. A system for executing an artificial neural network, 15 from the accelerator memory to the main memory\nthe system comprising: during performance of the intermediate computa\n a central processing unit (CPU ) to provide first input tions in the sequence of computations by the at least\n data ; one processing unit, and to control performance of\n a memory, operably coupled to the CPU , to store the first the sequence of computations by the at least one\n input data in a first partition, referenced by a first 20 processing unit.\n pointer, before computing a first layer of neurons of the 45. The computer system of claim 44, wherein the central\n artificial neural network ; processing unit is configured to receive the input data in\n a processing unit, operably coupled to the memory, to response to a user interaction .\n perform , during computation of the first layer of neu- 46. The computer system of claim 44, wherein :\n rons, at least one calculation on the first input data so 25 the central processing unit is configured to receive the\n as to generate first output data , the first output data input data at a first rate ; and\n representing an output of at least one neuron in the first the at least one processing unit is configured to perform\n layer of neurons ; and the sequence of computations at a second rate different\n a controller, operably coupled to the processing unit and than the first rate.\n the memory, to : 30 47. The computer system of claim 44, wherein the main\n store the first output data in a second partition of the memory is configured to store a copy of the output data\n memory, the second partition referenced by a second stored in the accelerator memory.\n pointer, and to swap the firstpointer with the second 48. The computer system of claim wherein an output\n pointer at the end of the computation of the first layer of at least one computation in the sequence of computations\n of neurons, such that the firstoutput data becomes an 35 represents an output of at least one neuron in an artificial\n input for a second layer of neurons of the artificial neural network .\n neural network, 49. The computer system of claim 44, wherein accelerator\n transfer the first output data to another memory during memory comprises:\n computation of the second layer of neurons, and a first memory partition to store parameters common to\n dictate an order of execution of instructions to the 40 all of the computations in the sequence of computa\n processing unit to perform the computation of the tions ; and\n first layer of neurons . a second memory partition to store data specific to at least\n 41. The system of claim 40 , wherein the processing unit one computation in the sequence of computations.\ncomprises a graphics processing unit . 50. The computer system of claim 44, wherein the con\n 42. The system of claim 40 , wherein the controller is 45 troller is configured to transfer the output data from the\nconfigured to send instructions for performing the at least accelerator memory to the main memory without transfer\none calculation to the processing unit. ring any of the intermediate results from the accelerator\n 43. The system of claim 40 , wherein the memory further memory to the main memory so as to reduce data transfer\ncomprises : via the bus.\n a third partition to store internal variables; and 50 51. The computer system of claim 44, wherein the con\n a fourth partition to store data used as input at a troller is configured to transfer at least a portion of the\n particular layer of neurons of the artificial neural output data from the accelerator memory to the main\n network. memory after the at least one processing unit has begun to\n 44. A computer system , comprising: perform another sequence of computations.\n a central processing unit to receive input data acquired 55 52. The computer system of claim 51 , wherein the con\n from an external system ; troller is configured to initiate transfer of the at least a\n main memory, operably coupled to the central processing portion of the input data and to transfer the at least a portion\n unit via a bus, to store the input data received by the of the output data in parallel with performance of at least\n central processing unit; one computation in the other sequence of computations by\n an accelerator, operably coupled to the central processing 60 the at least one processing unit .\n unit and the main memory via the bus, to receive at 53. The computer system of claim 44, wherein the con\n least a portion of the input data from the main memory , troller is configured to control execution of the sequence of\n the accelerator comprising : computations by the at least one processing unit .\n at least one processing unit to perform a sequence of 54. The computer system of claim 44, further comprising :\n computations representing an artificial neural net- 65 at least one of a video camera , a microphone, or a cell\n work on the at least a portion of the input data so as recording electrode, operably coupled to the central\n to generate output data, intermediate computations processing unit, to acquire the input data in real time .\n\f Case 7:26-mc-00324-DC Document 1-4 Filed 08/18/26 Page 22 of 22\n\n\n US RE48,438 E\n 21 22\n 55. The computer system of claim 1 , wherein the control\nler is configured to inform the central processing unit that\nthe sequence of computations is finished .\n 56. The computer system of claim 1 , wherein the control\nler is configured to reduce a processing load on the central 5\nprocessing unit.\n 57. The computer system of claim 1 , wherein the control\nler is configured to reduce interactions between the central\nprocessing unit and the accelerator.\n 10\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:19.475887-07:00","document_number":"1","attachment_number":4,"pacer_doc_id":"181037219899","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 3","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514518/","id":490514518,"tags":[],"absolute_url":"/docket/74667129/1/5/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.026310-07:00","date_modified":"2026-08-23T08:26:07.076059-07:00","sha1":"bee5accc4e167467ac858d8131e18fd36226454c","page_count":20,"file_size":1057521,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.5.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.5.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"","ocr_status":null,"date_upload":"2026-08-20T10:55:13.676508-07:00","document_number":"1","attachment_number":5,"pacer_doc_id":"181037219900","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 4","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514519/","id":490514519,"tags":[],"absolute_url":"/docket/74667129/1/6/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.039788-07:00","date_modified":"2026-08-23T01:58:44.566145-07:00","sha1":"f1bbb7fcfc392e79c0f9542fd3bd1e511252092d","page_count":24,"file_size":2940519,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.6.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.6.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 1 of 24\n\n\n\n\n EXHIBIT\n\n 5\n\fCase 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 2 of 24\n\n\n\n\n Attachment 1\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 3 of 24\nAO 88B (Rev. 06/09) Subpoena to Produce Documents, Information, or Objects or to Permit Inspection of Premises in a Civil Action\n\n\n UNITED STATES DISTRICT COURT\n for the\n __________\n Western District of __________\n Texas\n\n )\n Plaintiff )\n v. ) Civil Action No.\n )\n ) (If the action is pending in another district, state where:\n Defendant ) __________ District of __________ )\n\n SUBPOENA TO PRODUCE DOCUMENTS, INFORMATION, OR OBJECTS\n OR TO PERMIT INSPECTION OF PREMISES IN A CIVIL ACTION\n\nTo:\n\n Production: YOU ARE COMMANDED to produce at the time, date, and place set forth below the following\ndocuments, electronically stored information, or objects, and permit their inspection, copying, testing, or sampling of the\nmaterial:\n\n\n\n Place: Date and Time:\n\n\n\n Inspection of Premises: YOU ARE COMMANDED to permit entry onto the designated premises, land, or\nother property possessed or controlled by you at the time, date, and location set forth below, so that the requesting party\nmay inspect, measure, survey, photograph, test, or sample the property or any designated object or operation on it.\n\n Place: Date and Time:\n\n\n\n\n The provisions of Fed. R. Civ. P. 45(c), relating to your protection as a person subject to a subpoena, and Rule\n45 (d) and (e), relating to your duty to respond to this subpoena and the potential consequences of not doing so, are\nattached.\n\n\nDate:\n\n CLERK OF COURT\n OR\n\n Signature of Clerk or Deputy Clerk Attorney\u2019s signature\n\n\nThe name, address, e-mail, and telephone number of the attorney representing (name of party)\n , who issues or requests this subpoena, are:\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 4 of 24\nAO 88B (Rev. 06/09) Subpoena to Produce Documents, Information, or Objects or to Permit Inspection of Premises in a Civil Action (Page 2)\n\nCivil Action No.\n\n PROOF OF SERVICE\n (This section should not be filed with the court unless required by Fed. R. Civ. P. 45.)\n\n This subpoena for (name of individual and title, if any)\nwas received by me on (date) .\n\n I served the subpoena by delivering a copy to the named person as follows:\n\n\n on (date) ; or\n\n I returned the subpoena unexecuted because:\n .\n\n Unless the subpoena was issued on behalf of the United States, or one of its officers or agents, I have also\n tendered to the witness fees for one day\u2019s attendance, and the mileage allowed by law, in the amount of\n $ .\n\nMy fees are $ for travel and $ for services, for a total of $ .\n\n\n I declare under penalty of perjury that this information is true.\n\n\nDate:\n Server\u2019s signature\n\n\n\n Printed name and title\n\n\n\n\n Server\u2019s address\n\nAdditional information regarding attempted service, etc:\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 5 of 24\n AO 88B (Rev. 06/09) Subpoena to Produce Documents, Information, or Objects or to Permit Inspection of Premises in a Civil Action(Page 3)\n\n\n\n\n Federal Rule of Civil Procedure 45 (c), (d), and (e) (Effective 12/1/07)\n(c) Protecting a Person Subject to a Subpoena. (d) Duties in Responding to a Subpoena.\n (1) Avoiding Undue Burden or Expense; Sanctions. A party or (1) Producing Documents or Electronically Stored Information.\nattorney responsible for issuing and serving a subpoena must take These procedures apply to producing documents or electronically\nreasonable steps to avoid imposing undue burden or expense on a stored information:\nperson subject to the subpoena. The issuing court must enforce this (A) Documents. A person responding to a subpoena to produce\nduty and impose an appropriate sanction \u2014 which may include lost documents must produce them as they are kept in the ordinary\nearnings and reasonable attorney\u2019s fees \u2014 on a party or attorney course of business or must organize and label them to correspond to\nwho fails to comply. the categories in the demand.\n (2) Command to Produce Materials or Permit Inspection. (B) Form for Producing Electronically Stored Information Not\n (A) Appearance Not Required. A person commanded to produce Specified. If a subpoena does not specify a form for producing\ndocuments, electronically stored information, or tangible things, or electronically stored information, the person responding must\nto permit the inspection of premises, need not appear in person at the produce it in a form or forms in which it is ordinarily maintained or\nplace of production or inspection unless also commanded to appear in a reasonably usable form or forms.\nfor a deposition, hearing, or trial. (C) Electronically Stored Information Produced in Only One\n (B) Objections. A person commanded to produce documents or Form. The person responding need not produce the same\ntangible things or to permit inspection may serve on the party or electronically stored information in more than one form.\nattorney designated in the subpoena a written objection to (D) Inaccessible Electronically Stored Information. The person\ninspecting, copying, testing or sampling any or all of the materials or responding need not provide discovery of electronically stored\nto inspecting the premises \u2014 or to producing electronically stored information from sources that the person identifies as not reasonably\ninformation in the form or forms requested. The objection must be accessible because of undue burden or cost. On motion to compel\nserved before the earlier of the time specified for compliance or 14 discovery or for a protective order, the person responding must show\ndays after the subpoena is served. If an objection is made, the that the information is not reasonably accessible because of undue\nfollowing rules apply: burden or cost. If that showing is made, the court may nonetheless\n (i) At any time, on notice to the commanded person, the serving order discovery from such sources if the requesting party shows\nparty may move the issuing court for an order compelling production good cause, considering the limitations of Rule 26(b)(2)(C). The\nor inspection. court may specify conditions for the discovery.\n (ii) These acts may be required only as directed in the order, and (2) Claiming Privilege or Protection.\nthe order must protect a person who is neither a party nor a party\u2019s (A) Information Withheld. A person withholding subpoenaed\nofficer from significant expense resulting from compliance. information under a claim that it is privileged or subject to\n (3) Quashing or Modifying a Subpoena. protection as trial-preparation material must:\n (A) When Required. On timely motion, the issuing court must (i) expressly make the claim; and\nquash or modify a subpoena that: (ii) describe the nature of the withheld documents,\n (i) fails to allow a reasonable time to comply; communications, or tangible things in a manner that, without\n (ii) requires a person who is neither a party nor a party\u2019s officer revealing information itself privileged or protected, will enable the\nto travel more than 100 miles from where that person resides, is parties to assess the claim.\nemployed, or regularly transacts business in person \u2014 except that, (B) Information Produced. If information produced in response to a\nsubject to Rule 45(c)(3)(B)(iii), the person may be commanded to subpoena is subject to a claim of privilege or of protection as trial-\nattend a trial by traveling from any such place within the state where preparation material, the person making the claim may notify any\nthe trial is held; party that received the information of the claim and the basis for it.\n (iii) requires disclosure of privileged or other protected matter, if After being notified, a party must promptly return, sequester, or\nno exception or waiver applies; or destroy the specified information and any copies it has; must not use\n (iv) subjects a person to undue burden. or disclose the information until the claim is resolved; must take\n (B) When Permitted. To protect a person subject to or affected by reasonable steps to retrieve the information if the party disclosed it\na subpoena, the issuing court may, on motion, quash or modify the before being notified; and may promptly present the information to\nsubpoena if it requires: the court under seal for a determination of the claim. The person\n (i) disclosing a trade secret or other confidential research, who produced the information must preserve the information until\ndevelopment, or commercial information; the claim is resolved.\n (ii) disclosing an unretained expert\u2019s opinion or information that\ndoes not describe specific occurrences in dispute and results from (e) Contempt. The issuing court may hold in contempt a person\nthe expert\u2019s study that was not requested by a party; or who, having been served, fails without adequate excuse to obey the\n (iii) a person who is neither a party nor a party\u2019s officer to incur subpoena. A nonparty\u2019s failure to obey must be excused if the\nsubstantial expense to travel more than 100 miles to attend trial. subpoena purports to require the nonparty to attend or produce at a\n (C) Specifying Conditions as an Alternative. In the circumstances place outside the limits of Rule 45(c)(3)(A)(ii).\ndescribed in Rule 45(c)(3)(B), the court may, instead of quashing or\nmodifying a subpoena, order appearance or production under\nspecified conditions if the serving party:\n (i) shows a substantial need for the testimony or material that\ncannot be otherwise met without undue hardship; and\n (ii) ensures that the subpoenaed person will be reasonably\ncompensated.\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 6 of 24\n\n\n\n\n EXHIBIT A\n\n DEFINITIONS AND INSTRUCTIONS\n\n 1. The term \u201cNVIDIA GPUs\u201d means the Hopper, Ada Lovelace, Ampere, Turing,\n\nVolta, Pascal, Maxwell, Jetson, and Blackwell architectures of NVIDIA graphics processing units.\n\nFor avoidance of doubt, those architectures include the following devices: DGX line of\n\nsupercomputers and servers (including at least DGX B300, DGX B200, DGX GB200, DGX\n\nGB300, DGX Spark, DGX Station, DGX SuperPOD with GB300, DGX SuperPOD with GB200,\n\nDGX H200, DGX H100, DGX BasePOD, DGX SuperPOD with H200, DGX A100), HGX line of\n\nsupercomputers and servers (including at least HGX B300, HGX B200, HGX H100, HGX H200,\n\nEos SuperPOD), OVX line of supercomputers and servers (including at least OVX L40S), EGX\n\nline of supercomputers and servers (including at least EGX Server with Quadro RTX A6000, EGX\n\nServer with A40, EGX Server with Quadro RTX 8000, EGX Server with Quadro RTX 6000),\n\nGB300 NVL72, GB200 NVL72; Nvidia\u2019s GPU accelerators and superchips, including those with\n\nNVIDIA\u2019s Blackwell, Hopper, Ada Lovelace, Ampere, Turing, Volta, Pascal, and Maxwell GPU\n\narchitectures, including at least, RTX PRO 6000 Server Edition, RTX PRO 6000 Workstation,\n\nRTX PRO 6000 Max-Q Workstation, RTX PRO 5000, RTX PRO 4500, RTX PRO 4000, RTX\n\nPRO 3000, RTX PRO 2000, RTX PRO 1000, RTX PRO 500, GB300, GB200, H100, H200,\n\nGH200, GH100, L40, L40S, L4, RTX 6000, RTX 6000 Ada, RTX 5000, Ada, RTX 4500 Ada,\n\nRTX 4000 Ada, RTX 4000 SFF, RTX 3500, RTX 3000, RTX 2000, RTX 1000, RTX 500, RTX\n\n4090, RTX 4080 SUPER, RTX 4070 Ti SUPER, RTX 4070 SUPER, RTX 4070, RTX 4060 Ti,\n\nand RTX 4060, GeForce RTX 4090 Laptop GPU, GeForce RTX 4080 Laptop GPU, GeForce RTX\n\n4070 Laptop GPU, GeForce RTX 4060 Laptop GPU, GeForce RTX 4050 Laptop GPU, A100,\n\nA40, A30, A16, A10, A2, A800 40GB Active, RTX A6000, RTX A5500, RTX A5000, RTX\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 7 of 24\n\n\n\n\nA4500, RTX A4000, RTX A2000, RTX A2000 12GB, RTX A1000, RTX A400, RTX A5500,\n\nRTX A4500, RTX A3000 12GB, RTX A2000 8GB, RTX A1000 6GB, RTX A500, GeForce RTX\n\n3090 Ti, GeForce RTX 3090, GeForce RTX 3080 Ti, GeForce RTX 3080, GeForce RTX 3070 Ti,\n\nGeForce RTX 3070, GeForce RTX 3060 Ti, GeForce RTX 3060, GeForce RTX 3050 (8 GB),\n\nGeForce RTX 3050 (6 GB), GeForce RTX 3080 Ti Laptop GPU, GeForce RTX 3080 Laptop\n\nGPU, GeForce RTX 3070 Ti Laptop GPU, GeForce RTX 3070 Laptop GPU, GeForce RTX 3060\n\nLaptop GPU, GeForce RTX 3050 Ti Laptop GPU, GeForce RTX 3050 Laptop GPU, GeForce\n\nMX570 Laptop GPU, Tesla T4 GPUs, Quadro RTX 8000, Quadro RTX 6000, Quadro RTX 8000,\n\nQuadro RTX 6000, Quadro RTX 5000, Quadro RTX 4000, Quadro RTX 3000, Quadro T2000,\n\nT1000 8GB, T1200, Quadrio T1000, T1000 (4GB), T600, T550, T500 T400, T400 4GB, Titan\n\nRTX, GeForce RTX 2080 Ti, GeForce RTX 2080, Super, GeForce RTX 2080, GeForce RTX 2070\n\nSuper, GeForce RTX 2070, GeForce RTX 2060 Super, GeForce RTX 2060, GeForce RTX 2500,\n\nGeForce GTX 1660 Ti, GeForce GTX 1660 Super, GeForce GTX 1660, GeForce GTX 1650 Ti,\n\nGeForce GTX 1650 Super, GeForce GTX 1650 (G5), GeForce GTX 1650 (G6), GeForce GTX\n\n1650, GeForce GTX 1630, GeForce MX550, GeForce MX450, GeForce MX430, Tesla V100,\n\nQuadro GV100, Titan V GPU, Tesla P100, P40, P4, Quadro GP100, Quadro P6000, Quadro\n\nP5200, Quadro P5000, Quadro P4200, Quadro P4000, Quadro P3200, Quadro P3000, Quadro\n\nP2200, Quadro P2000, Quadro P1000, Quadro P620, Quadro P600, Quadro P520, Quadro P500,\n\nQuadro P400, Titan Xp, Titan X, GeForce GTX 1080 Ti, GeForce GTX 1080, GeForce GTX 1070\n\nTi, GeForce GTX 1070, GeForce GTX 1060, GeForce GTX 1050 Ti, GeForce GTX 1050,\n\nGeForce MX300, GeForce MX200, GeForce MX150, Tesla M60, M40, M10, Quadro M6000\n\n24GB, Quadro M6000 (12GB), Quadro M5000, Quadro M5000M, Quadro M5500, Quadro\n\nM4000, Quadro M4000M, Quadro M3000M, Quadro M2200, Quadro M2000, Quadro M2000M,\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 8 of 24\n\n\n\n\nQuadro M1200, Quadro M1000M, Quadro M620, Quadro M600M, Quadro M520, Quadro\n\nM500M, NVS 810, Tesla M6, GTX Titan X, GeForce GTX 980Ti, GeForce GTX 980, GeForce\n\nGTX 970, GeForce GTX 960, GeForce GTX 980M, GeForce GTX 970M, GeForce GTX 965M,\n\nGeForce GTX 960M, GeForce GTX 950M, GeForce GTX 750 Ti, GeForce GTX 750, GeForce\n\nMX130, and GeForce MX110; and Jetson modules, including at least the Jetson Thor Series,\n\nJetson Thor, Jetson T5000, Jetson T4000, Jetson AGX Orin Series, Jetson AGX Orin Developer\n\nKit, Jetson AGX Orin 64GB, Jetson AGX Orin Industrial, Jetson AGX Orin 32GB, Jetson Orin\n\nNX Series, Jetson Orin NX 16GB, Jetson Orin NX 8GB, Jetson Orin Nano Series, Jetson Orin\n\nNano Super Developer Kit, Jetson Orin Nano 8GB, Jetson Orin Nano 4GB, Jetson AGX Xavier\n\nSeries, Jetson AGX Xavier Industrial, Jetson AGX Xavier 64GB, Jetson AGX Xavier 32GB,\n\nJetson Xavier NX Series, Jetson Xavier NX 16GB, Jetson Xavier NX 8GB, Jetson TX2 Series,\n\nJetson TX2i, Jetson TX2, Jetson TX2 4GB, Jetson TX2 NX, Jetson Nano, any and all variations\n\nof the aforementioned products (including at least products having different options for number of\n\nGPUs).\n\n 2. The terms \u201cand\u201d and \u201cor\u201d are not intended to be read disjunctively but rather\n\nconjunctively unless the context of a particular request clearly indicates otherwise. \u201cOr\u201d should be\n\nunderstood to include and encompass \u201cand\u201d; and \u201cand\u201d should be understood to include and\n\nencompass \u201cor.\u201d\n\n 3. The terms \u201cany\u201d or \u201ceach\u201d should be understood to include and encompass \u201call.\u201d\n\n 4. The terms \u201cconcerning,\u201d \u201crelated to\u201d or \u201crelating to\u201d, and \u201cregarding\u201d and any\n\nvariation of these terms mean analyzing, alluding to, concerning, considering, commenting on,\n\nconsulting, comprising, containing, contradicting, describing, dealing with, discussing,\n\nestablishing, evidencing, identifying, involving, noting, recording, reporting on, relating to,\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 9 of 24\n\n\n\n\nreflecting, referring to, regarding, stating, showing, studying, mentioning, memorializing, or\n\npertaining to, directly or indirectly, in whole or in part.\n\n 5. The term \u201cCPU(s)\u201d means Central Processing Unit(s).\n\n 6. The term \u201cDocument(s)\u201d shall have the broadest meaning possible under Federal\n\nRules 26 and 34 and shall include without limitation: documents, Electronically Stored\n\nInformation, communications in written, electronic, and recorded form, and tangible things. A\n\ndraft or non-identical copy of a document shall be considered a separate document within the\n\nmeaning of the term \u201cdocument.\u201d Any comment, notation, or other marking shall be sufficient to\n\ndistinguish documents that are otherwise similar in appearance and to make them separate\n\ndocuments for purposes of your response. Any preliminary form, intermediate form, superseded\n\nversion, or amendment of any document is to be considered a separate document.\n\n 7. The term \u201cGPU(s)\u201d means Graphics Processing Unit(s).\n\n 8. The terms \u201cinclude\u201d and \u201cincluding\u201d mean including without limitation.\n\n 9. The term \u201cNVIDIA\u201d means Defendant NVIDIA Corporation, its predecessors,\n\npresent and former directors, officers, accountants, affiliates, attorneys, partners, managers, agents,\n\nemployees, representatives, in-house and outside counsel, and any other person or entity acting on\n\nbehalf of or under control of Defendant NVIDIA Corporation.\n\n 10. The term \u201cperson(s)\u201d means and includes natural persons and formal or informal\n\nentities and organizations, including public and private corporations, partnerships, professional\n\ncorporations, limited liability companies, business trusts, banking institutions, associations, firms,\n\njoint ventures, commissions, bureaus, departments, and any other legal entity, including\n\nany divisions, subsidiaries, departments, and other units thereof.\n\n 11. The term \u201cSource Code\u201d means human-readable instructions written in a\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 10 of 24\n\n\n\n\nprogramming language, including all comments, annotations, declarations, functions, classes, and\n\nother components used to define the behavior of a software program. For purposes of these\n\nrequests, \u201cSource Code\u201d includes all associated files necessary to understand, compile, and execute\n\nthe code, such as scripts, header files, makefiles, configuration files, and documentation. Unless\n\notherwise stated, \u201cSource Code\u201d includes all versions and revisions relevant to the time periods\n\nand subject matter described in each interrogatory.\n\n 12. The terms \u201cYou\u201d or \u201cYour\u201d refer to Google LLC, including but not limited to its\n\npredecessors, successors, parents, subsidiaries, divisions, affiliates, and all past or present\n\ndirectors, officers, partners, managers, employees, contractors, agents, representatives,\n\naccountants, consultants, in-house and outside counsel, and any other person or entity acting or\n\npurporting to act on its behalf or subject to its control. This definition expressly includes, without\n\nlimitation, any Google parent, subsidiary, affiliate, or other related entity that has used, licensed,\n\ndeployed, evaluated, or integrated NVIDIA GPUs or software.\n\n 13. The use of the singular form of any word includes the plural and vice versa.\n\n 14. These Requests seek the production of all documents, electronically stored\n\ninformation (\u201cESI\u201d), and tangible things in your possession, custody, or control, as that phrase is\n\nused in Federal Rule of Civil Procedure 34, as of the date of compliance with this subpoena and\n\nthat come into your possession, custody, or control at any time prior to production. This includes\n\nmaterials held by You directly, as well as by Your affiliates, subsidiaries, agents, representatives,\n\nor any other person or entity acting on Your behalf.\n\n 15. If You are aware of the existence (past or present) of any responsive documents,\n\nESI, or tangible items that are not in Your current possession, custody, or control, You must\n\nidentify such materials and provide:\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 11 of 24\n\n\n\n\n a. A description of the item(s);\n\n b. The name and contact information of the person or entity currently believed\n\n to have possession, custody, or control; and\n\n c. The reason You are unable to produce the material(s).\n\n 16. If You believe that no responsive documents, ESI, or tangible things exist in\n\nresponse to a particular request, You must state so in writing with respect to that request.\n\n 17. If You withhold any document, ESI, or portion thereof based on a claim of attorney-\n\nclient privilege, work product doctrine, or any other legal protection, You must produce a privilege\n\nlog that complies with Federal Rule of Civil Procedure 26(b)(5).\n\n 18. You must produce all documents and ESI: as they are kept in the usual course of\n\nbusiness or organized and labeled to correspond to the categories in this subpoena, as required\n\nunder FRCP 34(b)(2)(E); in their native electronic format (with original metadata intact) wherever\n\npossible, or as searchable, OCR-scanned PDFs with corresponding load files; with complete\n\nfamily groupings (e.g., attachments must be produced with their parent emails/documents); and in\n\nthe same folders or directories in which they were maintained, preserving original file structures\n\nand naming conventions.\n\n 19. You must maintain and produce a record of the source of each document or ESI\n\nitem produced, including:\n\n a. The file path or directory location;\n\n b. The name of the custodian (individual, team, or department) from whose\n files the document was collected;\n\n c. The system or platform (e.g., email server, shared drive, cloud service) from\n which the document was obtained.\n\nThis information may be provided in metadata load files, a source log, or other mutually agreed\n\nformat. This instruction is consistent with Federal Rule of Civil Procedure 34(b)(2)(E) and\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 12 of 24\n\n\n\n\nproportional discovery principles under Rule 26(b)(1). If any of the above information is not\n\nreasonably available or unduly burdensome to collect, You must so state and explain the basis for\n\nthat assertion.\n\n 20. For all ESI, You must preserve and produce standard metadata fields, including but\n\nnot limited to: filename, filepath, author, date created, date last modified, recipients, sender,\n\nsubject line (for emails), and document type. You must not degrade or alter metadata through\n\nprocessing or production.\n\n 21. You are under a continuing obligation to supplement or correct Your production if\n\nYou discover or obtain additional responsive materials prior to the close of discovery or the\n\nresolution of this matter.\n\n 22. Unless otherwise stated, the relevant period is from September 13, 2018 to the\n\npresent.\n\n 23. Unless otherwise stated, all requests herein are limited to documents, electronically\n\nstored information, and tangible things that relate to NVIDIA GPU-Acceleration Hardware or\n\nNVIDIA GPU-Acceleration Software that were:\n\n a. purchased, acquired, licensed, used, implemented, deployed, tested, or\n evaluated within the United States, or\n\n b. purchased, acquired, licensed, or used for the purpose of supporting,\n enabling, or operating any facility, system, team, data center, personnel,\n product, service, customer, or business activity located in or directed toward\n the United States.\n\nThis instruction is intended to encompass both U.S.-based activity and non-U.S. activity that\n\ndirectly supports or enables U.S. operations or usage.\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 13 of 24\n\n\n\n\n REQUESTS FOR PRODUCTION OF DOCUMENTS\n\n1. Documents sufficient to identify all software, frameworks, libraries, APIs, scripts, Source\n\n Code, configuration files, and custom code You use to perform computations on NVIDIA\n\n GPUs.\n\n2. Documents sufficient to show whether You use NVIDIA\u2019s Aerial, Clara Parabricks, cuBLAS,\n\n cuDNN, cuFFT, cuQuantum, cuSOLVER, cuSPARSE, Drive, DriveWorks, Holoscan, Isaac,\n\n Isaac Lab, Maxine, Memory Map, Merlin, Metropolis, Modulus, Monai, Morpheus, NeMo,\n\n PyTorch, RAPIDS, Riva, Runtime Driver, TensorFlow, TensorRT, Triton, VSS (Deepstream),\n\n or any other NVIDIA software as part of computations You perform using NVIDIA GPUs.\n\n3. Documents sufficient to show whether You use sample Source Code provided by NVIDIA as\n\n part of computations You perform using NVIDIA GPUs.\n\n4. Documents sufficient to show whether and how any software You use to perform\n\n computations on NVIDIA GPUs calls, invokes, interfaces with, wraps, depends on, sits on top\n\n of, modifies, extends, or implements functionality provided by CUDA, cuDNN, TensorRT,\n\n CUDA libraries, CUDA drivers, CUDA runtime, CUDA applications or frameworks or any\n\n other NVIDIA software.\n\n5. Documents sufficient to show the architecture, design, data flow, control flow, and execution\n\n flow of any system in which You use NVIDIA GPUs to perform computations, including\n\n diagrams, technical specifications, design documents, Powerpoints, slide decks, internal and\n\n external presentations, Source Code, configuration files, build files, deployment files, runtime\n\n logs, and profiler traces.\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 14 of 24\n\n\n\n\n6. Documents sufficient to show whether computations You performed using NVIDIA GPUs\n\n involved artificial neural networks, neural-network computational layers or computations with\n\n outputs as inputs for other neurons or layers.\n\n7. Documents sufficient to show whether You use a pointer to data stored in memory (e.g.\n\n memory bank or partition), using as an input to a subsequent computational layer the pointer\n\n to output data from a GPU computation, using pointers in neural network computations,\n\n swapping an input pointer with the pointer to data output from a GPU computation, pointer\n\n swapping, pointer rotation, buffer swapping, ping-pong buffers, double or triple buffering,\n\n alternating input/output buffers, or any other technique in which output data from one\n\n computation, layer, iteration, time step, or cycle becomes input data for a later computation,\n\n layer, iteration, time step, or cycle.\n\n8. Documents sufficient to show whether You store input data, output data, intermediate results,\n\n tensors, activations, weights, parameters, internal variables, GPU programs, kernels, textures,\n\n shaders, or other GPU-computation-related data in separate, partitioned, logical, physical,\n\n first/second, input/output, texture, shader, shared, global, device, host, pinned, GPU RAM,\n\n GPU cache(s), or unified memory regions (shared by CPU and GPU) when performing\n\n computations using NVIDIA GPUs.\n\n9. Documents sufficient to show how input data is received, acquired, stored, transferred, copied,\n\n streamed, prefetched, staged, queued, or loaded from CPU memory, host memory, system\n\n memory, storage, sensors, cameras, or other input sources to NVIDIA GPU memory\u2014\n\n including GPU RAM (e.g. GPU HBM, GDDR) and/or GPU cache(s)\u2014before, during, or in\n\n parallel with computations You perform using NVIDIA GPUs.\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 15 of 24\n\n\n\n\n10. Documents sufficient to show how output data from a GPU computation(s), intermediate\n\n results of GPU computations, tensors, buffers, activations, variables, or other computation\n\n results are stored, transferred, copied, streamed, written back, returned, accumulated, reused,\n\n or made available including asynchronously from NVIDIA GPU memory to CPU memory,\n\n host memory, system memory, storage, display, network, or another memory location before,\n\n during, or in parallel with computations You perform using NVIDIA GPUs\u2014and also\n\n including in the opposite direction, copying data from CPU or host or other memory to a queue\n\n for GPU computation while other GPU computations are occurring.\n\n11. Documents sufficient to show how computations You perform using NVIDIA GPUs are\n\n scheduled, ordered, controlled, queued, synchronized, parallelized, launched, interrupted,\n\n resumed, or executed, including through kernels, CUDA streams, CUDA graphs, events,\n\n threads, controllers, schedulers, compilers, runtimes, inference engines, run lists, run engines,\n\n or custom software.\n\n12. Documents sufficient to show whether and how user inputs, user commands, configuration\n\n changes, parameter changes, model changes, computational-element changes, input changes,\n\n interruptions, or display/output changes affect computations You perform using NVIDIA\n\n GPUs and/or queue them for GPU computation.\n\fCase 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 16 of 24\n\n\n\n\n Attachment 2\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 17 of 24\nAO 88A (Rev. 02/14) Subpoena to Testify at a Deposition in a Civil Action\n\n\n UNITED STATES DISTRICT COURT\n for the\n Western District of __________\n __________ Texas\n Neural AI, LLC\n )\n Plaintiff )\n v. ) Civil Action No.\n )\n )\n Defendant )\n\n SUBPOENA TO TESTIFY AT A DEPOSITION IN A CIVIL ACTION\n\nTo:\n\n (Name of person to whom this subpoena is directed)\n\n Testimony: YOU ARE COMMANDED to appear at the time, date, and place set forth below to testify at a\ndeposition to be taken in this civil action. If you are an organization, you must designate one or more officers, directors,\nor managing agents, or designate other persons who consent to testify on your behalf about the following matters, or\nthose set forth in an attachment:\n\n\n Place: Date and Time:\n\n\n\n The deposition will be recorded by this method:\n\n Production: You, or your representatives, must also bring with you to the deposition the following documents,\n electronically stored information, or objects, and must permit inspection, copying, testing, or sampling of the\n material:\n\n\n\n\n The following provisions of Fed. R. Civ. P. 45 are attached \u2013 Rule 45(c), relating to the place of compliance;\nRule 45(d), relating to your protection as a person subject to a subpoena; and Rule 45(e) and (g), relating to your duty to\nrespond to this subpoena and the potential consequences of not doing so.\n\nDate:\n CLERK OF COURT\n OR\n\n Signature of Clerk or Deputy Clerk Attorney\u2019s signature\n\nThe name, address, e-mail address, and telephone number of the attorney representing (name of party)\n , who issues or requests this subpoena, are:\n\n\n Notice to the person who issues or requests this subpoena\nIf this subpoena commands the production of documents, electronically stored information, or tangible things before\ntrial, a notice and a copy of the subpoena must be served on each party in this case before it is served on the person to\nwhom it is directed. Fed. R. Civ. P. 45(a)(4).\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 18 of 24\nAO 88A (Rev. 02/14) Subpoena to Testify at a Deposition in a Civil Action (Page 2)\n\nCivil Action No.\n\n PROOF OF SERVICE\n (This section should not be filed with the court unless required by Fed. R. Civ. P. 45.)\n\n I received this subpoena for (name of individual and title, if any)\non (date) .\n\n I served the subpoena by delivering a copy to the named individual as follows:\n\n\n on (date) ; or\n\n I returned the subpoena unexecuted because:\n .\n\n Unless the subpoena was issued on behalf of the United States, or one of its officers or agents, I have also\n tendered to the witness the fees for one day\u2019s attendance, and the mileage allowed by law, in the amount of\n $ .\n\nMy fees are $ for travel and $ for services, for a total of $ .\n\n\n I declare under penalty of perjury that this information is true.\n\n\nDate:\n Server\u2019s signature\n\n\n\n Printed name and title\n\n\n\n\n Server\u2019s address\n\nAdditional information regarding attempted service, etc.:\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 19 of 24\n\nAO 88A (Rev. 02/14) Subpoena to Testify at a Deposition in a Civil Action (Page 3)\n\n Federal Rule of Civil Procedure 45 (c), (d), (e), and (g) (Effective 12/1/13)\n(c) Place of Compliance. (i) disclosing a trade secret or other confidential research, development,\n or commercial information; or\n (1) For a Trial, Hearing, or Deposition. A subpoena may command a (ii) disclosing an unretained expert\u2019s opinion or information that does\nperson to attend a trial, hearing, or deposition only as follows: not describe specific occurrences in dispute and results from the expert\u2019s\n (A) within 100 miles of where the person resides, is employed, or study that was not requested by a party.\nregularly transacts business in person; or (C) Specifying Conditions as an Alternative. In the circumstances\n (B) within the state where the person resides, is employed, or regularly described in Rule 45(d)(3)(B), the court may, instead of quashing or\ntransacts business in person, if the person modifying a subpoena, order appearance or production under specified\n (i) is a party or a party\u2019s officer; or conditions if the serving party:\n (ii) is commanded to attend a trial and would not incur substantial (i) shows a substantial need for the testimony or material that cannot be\nexpense. otherwise met without undue hardship; and\n (ii) ensures that the subpoenaed person will be reasonably compensated.\n (2) For Other Discovery. A subpoena may command:\n (A) production of documents, electronically stored information, or (e) Duties in Responding to a Subpoena.\ntangible things at a place within 100 miles of where the person resides, is\nemployed, or regularly transacts business in person; and (1) Producing Documents or Electronically Stored Information. These\n (B) inspection of premises at the premises to be inspected. procedures apply to producing documents or electronically stored\n information:\n(d) Protecting a Person Subject to a Subpoena; Enforcement. (A) Documents. A person responding to a subpoena to produce documents\n must produce them as they are kept in the ordinary course of business or\n (1) Avoiding Undue Burden or Expense; Sanctions. A party or attorney must organize and label them to correspond to the categories in the demand.\nresponsible for issuing and serving a subpoena must take reasonable steps (B) Form for Producing Electronically Stored Information Not Specified.\nto avoid imposing undue burden or expense on a person subject to the If a subpoena does not specify a form for producing electronically stored\nsubpoena. The court for the district where compliance is required must information, the person responding must produce it in a form or forms in\nenforce this duty and impose an appropriate sanction\u2014which may include which it is ordinarily maintained or in a reasonably usable form or forms.\nlost earnings and reasonable attorney\u2019s fees\u2014on a party or attorney who (C) Electronically Stored Information Produced in Only One Form. The\nfails to comply. person responding need not produce the same electronically stored\n information in more than one form.\n (2) Command to Produce Materials or Permit Inspection. (D) Inaccessible Electronically Stored Information. The person\n (A) Appearance Not Required. A person commanded to produce responding need not provide discovery of electronically stored information\ndocuments, electronically stored information, or tangible things, or to from sources that the person identifies as not reasonably accessible because\npermit the inspection of premises, need not appear in person at the place of of undue burden or cost. On motion to compel discovery or for a protective\nproduction or inspection unless also commanded to appear for a deposition, order, the person responding must show that the information is not\nhearing, or trial. reasonably accessible because of undue burden or cost. If that showing is\n (B) Objections. A person commanded to produce documents or tangible made, the court may nonetheless order discovery from such sources if the\nthings or to permit inspection may serve on the party or attorney designated requesting party shows good cause, considering the limitations of Rule\nin the subpoena a written objection to inspecting, copying, testing, or 26(b)(2)(C). The court may specify conditions for the discovery.\nsampling any or all of the materials or to inspecting the premises\u2014or to\nproducing electronically stored information in the form or forms requested. (2) Claiming Privilege or Protection.\nThe objection must be served before the earlier of the time specified for (A) Information Withheld. A person withholding subpoenaed information\ncompliance or 14 days after the subpoena is served. If an objection is made, under a claim that it is privileged or subject to protection as trial-preparation\nthe following rules apply: material must:\n (i) At any time, on notice to the commanded person, the serving party (i) expressly make the claim; and\nmay move the court for the district where compliance is required for an (ii) describe the nature of the withheld documents, communications, or\norder compelling production or inspection. tangible things in a manner that, without revealing information itself\n (ii) These acts may be required only as directed in the order, and the privileged or protected, will enable the parties to assess the claim.\norder must protect a person who is neither a party nor a party\u2019s officer from (B) Information Produced. If information produced in response to a\nsignificant expense resulting from compliance. subpoena is subject to a claim of privilege or of protection as\n trial-preparation material, the person making the claim may notify any party\n (3) Quashing or Modifying a Subpoena. that received the information of the claim and the basis for it. After being\n notified, a party must promptly return, sequester, or destroy the specified\n (A) When Required. On timely motion, the court for the district where information and any copies it has; must not use or disclose the information\ncompliance is required must quash or modify a subpoena that: until the claim is resolved; must take reasonable steps to retrieve the\n information if the party disclosed it before being notified; and may promptly\n (i) fails to allow a reasonable time to comply; present the information under seal to the court for the district where\n (ii) requires a person to comply beyond the geographical limits compliance is required for a determination of the claim. The person who\nspecified in Rule 45(c); produced the information must preserve the information until the claim is\n (iii) requires disclosure of privileged or other protected matter, if no resolved.\nexception or waiver applies; or\n (iv) subjects a person to undue burden. (g) Contempt.\n (B) When Permitted. To protect a person subject to or affected by a The court for the district where compliance is required\u2014and also, after a\nsubpoena, the court for the district where compliance is required may, on motion is transferred, the issuing court\u2014may hold in contempt a person\nmotion, quash or modify the subpoena if it requires: who, having been served, fails without adequate excuse to obey the\n subpoena or an order related to it.\n\n\n For access to subpoena materials, see Fed. R. Civ. P. 45(a) Committee Note (2013).\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 20 of 24\n\n\n\n\n EXHIBIT A\n\n DEFINITIONS AND INSTRUCTIONS\n\n 24. The term \u201cNVIDIA GPUs\u201d means the Hopper, Ada Lovelace, Ampere, Turing,\n\nVolta, Pascal, Maxwell, Jetson, and Blackwell architectures of NVIDIA graphics processing units.\n\nFor avoidance of doubt, those architectures include the following devices: DGX line of\n\nsupercomputers and servers (including at least DGX B300, DGX B200, DGX GB200, DGX\n\nGB300, DGX Spark, DGX Station, DGX SuperPOD with GB300, DGX SuperPOD with GB200,\n\nDGX H200, DGX H100, DGX BasePOD, DGX SuperPOD with H200, DGX A100), HGX line of\n\nsupercomputers and servers (including at least HGX B300, HGX B200, HGX H100, HGX H200,\n\nEos SuperPOD), OVX line of supercomputers and servers (including at least OVX L40S), EGX\n\nline of supercomputers and servers (including at least EGX Server with Quadro RTX A6000, EGX\n\nServer with A40, EGX Server with Quadro RTX 8000, EGX Server with Quadro RTX 6000),\n\nGB300 NVL72, GB200 NVL72; Nvidia\u2019s GPU accelerators and superchips, including those with\n\nNVIDIA\u2019s Blackwell, Hopper, Ada Lovelace, Ampere, Turing, Volta, Pascal, and Maxwell GPU\n\narchitectures, including at least, RTX PRO 6000 Server Edition, RTX PRO 6000 Workstation,\n\nRTX PRO 6000 Max-Q Workstation, RTX PRO 5000, RTX PRO 4500, RTX PRO 4000, RTX\n\nPRO 3000, RTX PRO 2000, RTX PRO 1000, RTX PRO 500, GB300, GB200, H100, H200,\n\nGH200, GH100, L40, L40S, L4, RTX 6000, RTX 6000 Ada, RTX 5000, Ada, RTX 4500 Ada,\n\nRTX 4000 Ada, RTX 4000 SFF, RTX 3500, RTX 3000, RTX 2000, RTX 1000, RTX 500, RTX\n\n4090, RTX 4080 SUPER, RTX 4070 Ti SUPER, RTX 4070 SUPER, RTX 4070, RTX 4060 Ti,\n\nand RTX 4060, GeForce RTX 4090 Laptop GPU, GeForce RTX 4080 Laptop GPU, GeForce RTX\n\n4070 Laptop GPU, GeForce RTX 4060 Laptop GPU, GeForce RTX 4050 Laptop GPU, A100,\n\nA40, A30, A16, A10, A2, A800 40GB Active, RTX A6000, RTX A5500, RTX A5000, RTX\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 21 of 24\n\n\n\n\nA4500, RTX A4000, RTX A2000, RTX A2000 12GB, RTX A1000, RTX A400, RTX A5500,\n\nRTX A4500, RTX A3000 12GB, RTX A2000 8GB, RTX A1000 6GB, RTX A500, GeForce RTX\n\n3090 Ti, GeForce RTX 3090, GeForce RTX 3080 Ti, GeForce RTX 3080, GeForce RTX 3070 Ti,\n\nGeForce RTX 3070, GeForce RTX 3060 Ti, GeForce RTX 3060, GeForce RTX 3050 (8 GB),\n\nGeForce RTX 3050 (6 GB), GeForce RTX 3080 Ti Laptop GPU, GeForce RTX 3080 Laptop\n\nGPU, GeForce RTX 3070 Ti Laptop GPU, GeForce RTX 3070 Laptop GPU, GeForce RTX 3060\n\nLaptop GPU, GeForce RTX 3050 Ti Laptop GPU, GeForce RTX 3050 Laptop GPU, GeForce\n\nMX570 Laptop GPU, Tesla T4 GPUs, Quadro RTX 8000, Quadro RTX 6000, Quadro RTX 8000,\n\nQuadro RTX 6000, Quadro RTX 5000, Quadro RTX 4000, Quadro RTX 3000, Quadro T2000,\n\nT1000 8GB, T1200, Quadrio T1000, T1000 (4GB), T600, T550, T500 T400, T400 4GB, Titan\n\nRTX, GeForce RTX 2080 Ti, GeForce RTX 2080, Super, GeForce RTX 2080, GeForce RTX 2070\n\nSuper, GeForce RTX 2070, GeForce RTX 2060 Super, GeForce RTX 2060, GeForce RTX 2500,\n\nGeForce GTX 1660 Ti, GeForce GTX 1660 Super, GeForce GTX 1660, GeForce GTX 1650 Ti,\n\nGeForce GTX 1650 Super, GeForce GTX 1650 (G5), GeForce GTX 1650 (G6), GeForce GTX\n\n1650, GeForce GTX 1630, GeForce MX550, GeForce MX450, GeForce MX430, Tesla V100,\n\nQuadro GV100, Titan V GPU, Tesla P100, P40, P4, Quadro GP100, Quadro P6000, Quadro\n\nP5200, Quadro P5000, Quadro P4200, Quadro P4000, Quadro P3200, Quadro P3000, Quadro\n\nP2200, Quadro P2000, Quadro P1000, Quadro P620, Quadro P600, Quadro P520, Quadro P500,\n\nQuadro P400, Titan Xp, Titan X, GeForce GTX 1080 Ti, GeForce GTX 1080, GeForce GTX 1070\n\nTi, GeForce GTX 1070, GeForce GTX 1060, GeForce GTX 1050 Ti, GeForce GTX 1050,\n\nGeForce MX300, GeForce MX200, GeForce MX150, Tesla M60, M40, M10, Quadro M6000\n\n24GB, Quadro M6000 (12GB), Quadro M5000, Quadro M5000M, Quadro M5500, Quadro\n\nM4000, Quadro M4000M, Quadro M3000M, Quadro M2200, Quadro M2000, Quadro M2000M,\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 22 of 24\n\n\n\n\nQuadro M1200, Quadro M1000M, Quadro M620, Quadro M600M, Quadro M520, Quadro\n\nM500M, NVS 810, Tesla M6, GTX Titan X, GeForce GTX 980Ti, GeForce GTX 980, GeForce\n\nGTX 970, GeForce GTX 960, GeForce GTX 980M, GeForce GTX 970M, GeForce GTX 965M,\n\nGeForce GTX 960M, GeForce GTX 950M, GeForce GTX 750 Ti, GeForce GTX 750, GeForce\n\nMX130, and GeForce MX110; and Jetson modules, including at least the Jetson Thor Series,\n\nJetson Thor, Jetson T5000, Jetson T4000, Jetson AGX Orin Series, Jetson AGX Orin Developer\n\nKit, Jetson AGX Orin 64GB, Jetson AGX Orin Industrial, Jetson AGX Orin 32GB, Jetson Orin\n\nNX Series, Jetson Orin NX 16GB, Jetson Orin NX 8GB, Jetson Orin Nano Series, Jetson Orin\n\nNano Super Developer Kit, Jetson Orin Nano 8GB, Jetson Orin Nano 4GB, Jetson AGX Xavier\n\nSeries, Jetson AGX Xavier Industrial, Jetson AGX Xavier 64GB, Jetson AGX Xavier 32GB,\n\nJetson Xavier NX Series, Jetson Xavier NX 16GB, Jetson Xavier NX 8GB, Jetson TX2 Series,\n\nJetson TX2i, Jetson TX2, Jetson TX2 4GB, Jetson TX2 NX, Jetson Nano, any and all variations\n\nof the aforementioned products (including at least products having different options for number of\n\nGPUs).\n\n 25. The terms \u201cand\u201d and \u201cor\u201d are not intended to be read disjunctively but rather\n\nconjunctively unless the context of a particular request clearly indicates otherwise. \u201cOr\u201d should be\n\nunderstood to include and encompass \u201cand\u201d; and \u201cand\u201d should be understood to include and\n\nencompass \u201cor.\u201d\n\n 26. The terms \u201cany\u201d or \u201ceach\u201d should be understood to include and encompass \u201call.\u201d\n\n 27. The terms \u201cconcerning,\u201d \u201crelated to\u201d or \u201crelating to\u201d, and \u201cregarding\u201d and any\n\nvariation of these terms mean analyzing, alluding to, concerning, considering, commenting on,\n\nconsulting, comprising, containing, contradicting, describing, dealing with, discussing,\n\nestablishing, evidencing, identifying, involving, noting, recording, reporting on, relating to,\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 23 of 24\n\n\n\n\nreflecting, referring to, regarding, stating, showing, studying, mentioning, memorializing, or\n\npertaining to, directly or indirectly, in whole or in part.\n\n 28. The term \u201cCPU(s)\u201d means Central Processing Unit(s).\n\n 29. The term \u201cGPU(s)\u201d means Graphics Processing Unit(s).\n\n 30. The terms \u201cinclude\u201d and \u201cincluding\u201d mean including without limitation.\n\n 31. The term \u201cNVIDIA\u201d means Defendant NVIDIA Corporation, its predecessors,\n\npresent and former directors, officers, accountants, affiliates, attorneys, partners, managers, agents,\n\nemployees, representatives, in-house and outside counsel, and any other person or entity acting on\n\nbehalf of or under control of Defendant NVIDIA Corporation.\n\n 32. The term \u201cperson(s)\u201d means and includes natural persons and formal or informal\n\nentities and organizations, including public and private corporations, partnerships, professional\n\ncorporations, limited liability companies, business trusts, banking institutions, associations, firms,\n\njoint ventures, commissions, bureaus, departments, and any other legal entity, including\n\nany divisions, subsidiaries, departments, and other units thereof.\n\n 33. The term \u201cSource Code\u201d means human-readable instructions written in a\n\nprogramming language, including all comments, annotations, declarations, functions, classes, and\n\nother components used to define the behavior of a software program. For purposes of these topics,\n\n\u201cSource Code\u201d includes all associated files necessary to understand, compile, and execute the\n\ncode, such as scripts, header files, makefiles, configuration files, and documentation. Unless\n\notherwise stated, \u201cSource Code\u201d includes all versions and revisions relevant to the time periods\n\nand subject matter described in each interrogatory.\n\n 34. The terms \u201cYou,\u201d or \u201cYour\u201d refer to Google LLC, including but not limited to its\n\npredecessors, successors, parents, subsidiaries, divisions, affiliates, and all past or present\n\f Case 7:26-mc-00324-DC Document 1-6 Filed 08/18/26 Page 24 of 24\n\n\n\n\ndirectors, officers, partners, managers, employees, contractors, agents, representatives,\n\naccountants, consultants, in-house and outside counsel, and any other person or entity acting or\n\npurporting to act on its behalf or subject to its control. This definition expressly includes, without\n\nlimitation, any Google parent, subsidiary, affiliate, or other related entity that has used, licensed,\n\ndeployed, evaluated, or integrated NVIDIA Hardware and/or NVIDIA Software.\n\n 35. The use of the singular form of any word includes the plural and vice versa.\n\n DEPOSITION TOPICS\n\n1. The NVIDIA software and libraries You use to perform computations, including but not\n\n limited to NVIDIA\u2019s Aerial, Clara Parabricks, cuBLAS, cuDNN, cuFFT, cuQuantum,\n\n cuSOLVER, cuSPARSE, Drive, DriveWorks, Holoscan, Isaac, Isaac Lab, Maxine, Memory\n\n Map, Merlin, Metropolis, Modulus, Monai, Morpheus, NeMo, PyTorch, RAPIDS, Riva,\n\n Runtime Driver, TensorFlow, TensorRT, Triton, VSS (Deepstream).\n\n2. The NVIDIA sample Source Code You use, in whole or in part, to conduct computations.\n\n3. Your customizations and/or data inputs to NVIDIA software that alter the way in which\n\n NVIDIA software performs computations and/or a description of the data input to NVIDIA\n\n software on which computations are run.\n\n4. Identification of Your software that uses NVIDIA GPUs to perform computations.\n\n5. Using Your software, the ways in which output data from a GPU computation(s), including\n\n intermediate results of GPU computations are stored, referenced by a pointer, transferred,\n\n copied, streamed, written back, returned, accumulated, reused, or made available including\n\n asynchronously from NVIDIA GPU memory to CPU memory, host memory, system memory,\n\n storage, display, network, or another memory location before, during, or in parallel with\n\n computations performed using NVIDIA GPUs.\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:15.543099-07:00","document_number":"1","attachment_number":6,"pacer_doc_id":"181037219901","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 5","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514520/","id":490514520,"tags":[],"absolute_url":"/docket/74667129/1/7/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.052796-07:00","date_modified":"2026-08-23T08:26:07.812612-07:00","sha1":"0997e382262f7abf2c20d6f8a1410898f2b545ff","page_count":3,"file_size":661186,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.7.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.7.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"","ocr_status":null,"date_upload":"2026-08-20T10:55:16.787707-07:00","document_number":"1","attachment_number":7,"pacer_doc_id":"181037219902","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 6","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514521/","id":490514521,"tags":[],"absolute_url":"/docket/74667129/1/8/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.066641-07:00","date_modified":"2026-08-23T08:26:16.873588-07:00","sha1":"50289b533ab8c9cd212225550835defab3eaa559","page_count":18,"file_size":219834,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.8.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.8.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 1 of 18\n\n\n\n\n EXHIBIT\n\n 7\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 2 of 18\n\n\n\n\n UNITED STATES DISTRICT COURT\n FOR THE WESTERN DISTRICT OF TEXAS\n MIDLAND-ODESSA DIVISION\nNEURAL AI, LLC )\n )\n )\n Plaintiff, )\nv. ) Civil Action No. 7:24-cv-00221\n )\nNVIDIA CORPORATION )\n ) JURY TRIAL DEMANDED\n )\n Defendant. )\n\n\n PLAINTIFF\u2019S AMENDED DISCLOSURE OF ASSERTED CLAIMS AND FINAL\nINFRINGEMENT CONTENTIONS PURSUANT TO THE COURT\u2019S STANDING ORDER\n GOVERNING PATENT PROCEEDINGS\n\n Pursuant to the Court\u2019s December 2, 2025 Order (Dkt. 132), the First Amended Scheduling\n\n Order (Dkt. 135), and the Parties December 29, 2025 Joint Stipulation (Dkt. 136), Plaintiff Neural\n\n AI, LLC (\u201cNeural AI\u201d or \u201cPlaintiff\u201d) provides the following Disclosure of Asserted Claims and\n\n Final Infringement Contentions (\u201cDisclosure\u201d) as to U.S. Patent Nos. 8,648,867 (\u201cthe \u2019867\n\n Patent\u201d), RE49,461 (\u201cthe \u2019461 Patent\u201d), and RE48,438 (\u201cthe \u2019438 Patent\u201d) (collectively, the\n\n \u201cAsserted Patents\u201d or \u201cPatents-in-Suit\u201d) against Defendant Nvidia Corporation (\u201cNvidia\u201d or\n\n \u201cDefendant\u201d). This Disclosure is made solely for the purpose of this action.\n\n Pursuant to the Court\u2019s December 2, 2025 Order (Dkt. 132), Plaintiff identifies source code\n\n for each accused instrumentality based on Nvidia\u2019s productions prior to November 30, 2025.\n\n Nvidia continues to produce source code on a rolling basis. Plaintiff therefore expressly reserves\n\n the right to serve additional or supplemental claim chart exhibits identifying newly produced or\n\n previously unavailable source code that satisfies the asserted claim elements, including after\n\n service of this Disclosure. Moreover, Plaintiff\u2019s investigation regarding infringement and\n\n additional potential grounds of infringement is ongoing. Nvidia\u2019s has not produced all necessary\n\n 1\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 3 of 18\n\n\n\ntechnical documents or source code sufficient to show the operation of the Accused Products, and\n\nkey categories of technical materials, including source code, remain outstanding. See, e.g., Dkt.\n\n103, 125. This Disclosure is therefore based upon information that Plaintiff has been able to obtain\n\nand review to date, together with its good-faith beliefs regarding the Accused Products and their\n\noperation, and is made without prejudice to Plaintiff\u2019s right to supplement or amend its Disclosure\n\nas additional facts are ascertained, discovery is conducted, code is reviewed, analysis is done, and\n\nresearch is completed. Plaintiff reserves the right to amend and/or supplement its infringement\n\ncontentions as additional information becomes available.\n\n For each Asserted Patent, Plaintiff identifies the following Accused Products of which it is\n\ncurrently aware. The identification of Accused Products is based on Plaintiff\u2019s research and\n\nanalysis to date, without the benefit of full discovery. Indeed, Nvidia has not yet complied with\n\nits obligation under the OGP to produce sufficient \u201ctechnical documents, including software where\n\napplicable, sufficient to show the operation of the accused product(s).\u201d See, e.g., Dkt. 103, 125.\n\nNvidia has continued to belatedly produce source code well into the fact discovery period\u2014\n\nincluding most recently on January 13, 2026\u2014and has not produced related technical documents,\n\nand Plaintiff has been required to repeatedly press Nvidia to obtain these late and piecemeal\n\nproductions. As a result, Plaintiff\u2019s current identification of Accused Products is necessarily based\n\non publicly available and otherwise accessible information. Accordingly, Plaintiff\u2019s current\n\nidentification is based on publicly available and otherwise accessible information. Plaintiff\n\nexpressly reserves the right to amend or supplement these contentions\u2014including by identifying\n\nadditional Accused Products or asserting additional bases for infringement\u2014under the applicable\n\nrules and any Court orders, including to reflect future productions by Nvidia.\n\n Accused Products. The Accused Products, as described in the accompanying Exhibits 1\u2013\n\n599 and any later-served amended or supplemental Exhibits, comprise integrated combinations of\n\n 2\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 4 of 18\n\n\n\nNvidia\u2019s software and hardware that together implement GPU-accelerated computing. These\n\ninclude Nvidia\u2019s GPU accelerators and superchips; Nvidia\u2019s computers, supercomputers, data\n\ncenters, servers, and workstations incorporating those GPUs; and the full Nvidia software stack\n\nthat operates on and controls that hardware to enable accelerated execution.\n\n Based on its present understanding of Nvidia\u2019s infringing software architecture and how\n\nthe accused functionality is implemented across Nvidia\u2019s integrated hardware and software stack,\n\nNeural AI has organized its infringement charts by Nvidia application in Exhibits 100-199. These\n\napplication charts further reference sub-charts identifying hardware described in Exhibits 1-99 as\n\nwell as software and libraries described in Exhibits 200-599. The sub charts are broken out as\n\nfollows: Exhibits 1\u201399 include hardware such as Nvidia\u2019s GPU accelerators and superchips, and\n\nNvidia\u2019s computers, supercomputers, data centers, servers, workstations that implement its GPU\n\naccelerators and superchips, coupling of some of this hardware to CPUs, as well as information on\n\nNvidia\u2019s infringing software products and CUDA code. Exhibits 100-199 include Nvidia\u2019s\n\napplication frameworks and platforms. Application frameworks and platforms processed by the\n\nhardware, in turn, call on lower-level Nvidia software. Exhibits 200\u2013299 include Nvidia\u2019s\n\nmachine-learning frameworks and inference platforms used by these applications, including\n\nPyTorch and TensorRT. Exhibits 300\u2013399 include Nvidia\u2019s neural-network primitive libraries,\n\nacceleration libraries, and functions, including cuDNN and related components. Exhibits 400\u2013499\n\ninclude Nvidia\u2019s mathematical libraries. Exhibits 500\u2013599 include low-level CUDA runtime,\n\ndriver, memory-management components, memory maps, and sub-component code used in the\n\nCUDA stack.\n\n This organization reflects Neural AI\u2019s present understanding of Nvidia\u2019s software\n\narchitecture. Nvidia has not produced a complete source-code production for any bucket or\n\ncategory, and Neural AI therefore expressly reserves the right to chart additional software,\n\n 3\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 5 of 18\n\n\n\nlibraries, or components, and to modify or supplement its chart organization and infringement\n\ntheories as discovery continues. Moreover, the charts provided within each category are\n\nrepresentative of other similar Nvidia software, libraries, and components within that same\n\ncategory. Neural AI has charted exemplar implementations rather than every produced file, and\n\nreserves the right to rely on other Nvidia software and libraries within the same category as\n\nadditional accused instrumentalities.\n\n In further details, the Accused Products include, without limitation, the following: Nvidia\u2019s\n\nGPU accelerators and superchips, including those with Nvidia\u2019s \u201cBlackwell,\u201d \u201cHopper,\u201d \u201cAda\n\nLovelace,\u201d \u201cAmpere,\u201d \u201cTuring,\u201d \u201cVolta,\u201d \u201cPascal,\u201d and \u201cMaxwell\u201d GPU architectures. These\n\nGPUs and superchips implement, and are specifically designed for, GPU-acceleration for artificial\n\nintelligence and neural networks.\n\n Nvidia\u2019s Blackwell GPUs include RTX PRO 6000 Server Edition, RTX PRO 6000\n\nWorkstation, RTX PRO 6000 Max-Q Workstation, RTX PRO 6000, RTX PRO 5000, RTX PRO\n\n4500, RTX PRO 4000, RTX PRO 3000, RTX PRO 2000, RTX PRO 1000, RTX PRO 500, RTX\n\n5090, RTX 5090 D, RTX 5080, RTX 5070 Ti, RTX 5070, RTX 5060, RTX 5060 Ti, RTX 5050,\n\nRTX 5080 Laptop, RTX 5090 Laptop, RTX 5070 Ti Laptop, RTX 5060 Laptop, RTX 5070\n\nLaptop, and RTX 5050 Laptop. In addition, Nvidia\u2019s superchips that implement GPU accelerators\n\ninclude the GB300 and GB200.\n\n Nvidia\u2019s Hopper GPUs include the H100 and H200 GPUs, including by not limited to\n\nPCle, SXM, and NVL models. In addition, Nvidia\u2019s superchips that implement GPU accelerators\n\ninclude the GH200, or Grace Hopper Superchip, which implements the Hopper-GPU architecture.\n\n Nvidia\u2019s Ada Lovelace (or Lovelace) GPUs include Nvidia Data Center GPUs, including\n\nL40, L40S, and L4 GPUs; Nvidia Workstation and Professional Laptop GPUs, including RTX\n\nAda Generations series GPUs and Laptop GPUs (including RTX 6000, RTX 6000 Ada, RTX 5000\n\n 4\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 6 of 18\n\n\n\nAda, RTX 4500 Ada, RTX 4050, RTX 4000 Ada, RTX 4000 SFF, RTX 3500, RTX 3050, RTX\n\n3000, RTX 2000, RTX 1000, RTX 500); and GeForce RTX 40 series GPUs and Laptop GPUs\n\n(RTX 4090, RTX 4080 SUPER, RTX 4070 Ti SUPER, RTX 4070 SUPER, RTX 4070, RTX 4060\n\nTi, and RTX 4060; GeForce RTX 4090 Laptop GPU, GeForce RTX 4080 Laptop GPU, GeForce\n\nRTX 4070 Laptop GPU, GeForce RTX 4060 Laptop GPU, GeForce RTX 4050 Laptop GPU).\n\n Nvidia\u2019s Ampere GPUs include Nvidia Data Center GPUs, including A100, A40, A30,\n\nA16, A10, and A2 GPUs; Nvidia Workstation and Professional Laptop GPUs, including RTX A\n\nseries GPUs and Laptop GPUs (A800 40GB Active, RTX A6000, RTX A5500, RTX A5000, RTX\n\nA4500, RTX A4000, RTX A2000, RTX A2000 12GB, RTX A1000, RTX A400, RTX A5500,\n\nRTX A4500, RTX A3000 12GB, RTX A2000 8GB, RTX A1000 6GB, RTX A500); GeForce\n\nRTX 30 series GPUs and Laptop GPUs (GeForce RTX 3090 Ti, GeForce RTX 3090, GeForce\n\nRTX 3080 Ti, GeForce RTX 3080, GeForce RTX 3070 Ti, GeForce RTX 3070, GeForce RTX\n\n3060 Ti, GeForce RTX 3060, GeForce RTX 3050 (8 GB), GeForce RTX 3050 (6 GB), GeForce\n\nRTX 3080 Ti Laptop GPU, GeForce RTX 3080 Laptop GPU, GeForce RTX 3070 Ti Laptop GPU,\n\nGeForce RTX 3070 Laptop GPU, GeForce RTX 3060 Laptop GPU, GeForce RTX 3050 Ti Laptop\n\nGPU, GeForce RTX 3050 Laptop GPU); and GeForce MX570 Laptop GPU.\n\n Nvidia\u2019s Turing GPUs include Nvidia Data Center GPUs, including Tesla T4 GPUs and\n\nQuadro RTX 8000 (passive) and Quadro RTX 6000 (passive) GPUs; Nvidia Workstation and\n\nProfessional Laptop GPUs, including T series GPUs and Laptop GPUs, Quadro T series Laptop\n\nGPUs, and Quadro RTX series GPUs and Laptop GPUs (Quadro RTX 8000, Quadro RTX 6000,\n\nQuadro RTX 5000, Quadro RTX 4000, Quadro RTX 3000, Quadro T2000, T1000 8GB, T1200,\n\nQuadrio T1000, T1000 (4GB), T600, T550, T500 T400, T400 4GB); Titan series Titan RTX GPU;\n\nGeForce RTX 20 series GPUs and Laptop GPUs (GeForce RTX 2080 Ti, GeForce RTX 2080\n\nSuper, GeForce RTX 2080, GeForce RTX 2070 Super, GeForce RTX 2070, GeForce RTX 2060\n\n 5\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 7 of 18\n\n\n\nSuper, GeForce RTX 2060, GeForce RTX 2500); GeForce GTX 16 series GPUs and Laptop GPUs\n\n(GeForce GTX 1660 Ti, GeForce GTX 1660 Super, GeForce GTX 1660, GeForce GTX 1650 Ti,\n\nGeForce GTX 1650 Super, GeForce GTX 1650 (G5), GeForce GTX 1650 (G6), GeForce GTX\n\n1650, GeForce GTX 1630); and GeForce MX550, MX450, and MX430 Laptop GPUs.\n\n Nvidia\u2019s Volta GPUs include Nvidia Data Center GPUs, including the Tesla V100 GPU;\n\nNvidia Workstation GPUs, including Quadro GV100; and Titan series Titan V GPU.\n\n Nvidia\u2019s Pascal GPUs include Nvidia Data Center GPUs, including Tesla P100, P40, and\n\nP4 GPUs; Nvidia Workstation and Professional Laptop GPUs, including the Quadro GP100 GPU\n\nand Quadro P series GPUs and Laptop GPUs (Quadro P6000, Quadro P5200, Quadro P5000,\n\nQuadro P4200, Quadro P4000, Quadro P3200, Quadro P3000, Quadro P2200, Quadro P2000,\n\nQuadro P1000, Quadro P620, Quadro P600, Quadro P520, Quadro P500, Quadro P400); Titan\n\nseries Titan Xp and Titan X GPUs; GeForce GTX 10 series GPUs and Laptop GPUs (GeForce\n\nGTX 1080 Ti, GeForce GTX 1080, GeForce GTX 1070 Ti, GeForce GTX 1070, GeForce GTX\n\n1060, GeForce GTX 1050 Ti, GeForce GTX 1050); and GeForce MX300 series, MX200 series,\n\nand MX150 Laptop GPUs.\n\n Nvidia\u2019s Maxwell GPUs include Nvidia Data Center GPUs, including Tesla M60, M40,\n\nand M10 GPUs; Nvidia Workstation and Professional Laptop GPUs, including Quadro M series\n\nGPUs and Laptop GPUs (Quadro M6000 24GB, Quadro M6000 (12GB), Quadro M5000, Quadro\n\nM5000M, Quadro M5500, Quadro M4000, Quadro M4000M, Quadro M3000M, Quadro M2200,\n\nQuadro M2000, Quadro M2000M, Quadro M1200, Quadro M1000M, Quadro M620, Quadro\n\nM600M, Quadro M520, Quadro M500M), the NVS 810 GPU, and Tesla M6 series Laptop GPUs;\n\nTitan series GTX Titan X GPU; GeForce GTX 900 series GPUs and Laptop GPUs (GeForce GTX\n\n980Ti, GeForce GTX 980, GeForce GTX 970, GeForce GTX 960, GeForce GTX 980M, GeForce\n\nGTX 970M, GeForce GTX 965M, GeForce GTX 960M, GeForce GTX 950M); GeForce GTX\n\n 6\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 8 of 18\n\n\n\n700 series GPUs and Laptop GPUs (GeForce GTX 750 Ti, GeForce GTX 750); and GeForce\n\nMX130 series and MX110 Laptop GPUs.\n\n The Accused Products further include Nvidia\u2019s computers, supercomputers, data centers,\n\nservers, and workstations that implement its GPU accelerators and superchips. These computer\n\nhardware systems include: the DGX line of supercomputers, the HGX line of supercomputers, the\n\nOVX line of supercomputers, and the EGX line of servers for data centers and edge devices.\n\nNvidia\u2019s DGX supercomputers include the DGX B300, DGX B200, DGX GB200, DGX GB300,\n\nDGX Spark, DGX Station, DGX SuperPOD with GB300, DGX SuperPOD with GB200, DGX\n\nH200, DGX BasePOD, DGX A100, and DGX SuperPOD with DGX GB200. Nvidia\u2019s HGX\n\nincludes least the HGX B300, HGX B200, HGX H100, HGX H200, and EoS SuperPOD. And\n\nNvidia\u2019s EGX includes at least EGX Server with Quadro RTX A6000, EGX Server with A40,\n\nEGX Server with Quadro RTX 8000, EGX Server with Quadro RTX 6000), GB300 NVL72,\n\nGB200 NVL72.\n\n The Accused Products include Nvidia\u2019s software, platforms, libraries, and services for\n\naccelerated computing. These products include, without limitation, application frameworks,\n\nplatforms, and domains such as NVIDIA Drive, Isaac, Holoscan, RAPIDS, NVBlox, NeMo,\n\nMerlin, Modulus, MONAI, Morpheus, Riva, Maxine, Clara, Metropolis, Tokkio, Avatar, NIM\n\nMicroservices, Omniverse, Clara Train, TAO, DRIVE Sim, DLSS, PhysX, OptiX, Texture Tools,\n\nJetPack, DeepStream, DOCA, Magnum IO, Aerial, BioNeMo, CUDA-X HPC, Unified Compute\n\nFramework, AI Enterprise, the DGX Platform, NGC, and AI Foundation Models. Application\n\nframeworks and platforms processed by the hardware, in turn, call on lower-level Nvidia software.\n\nThe Accused Products further include machine-learning frameworks and inference platforms such\n\nas PyTorch, TensorRT, Triton, TensorFlow, Torch-TensorRT, JAX, and Spark. They also include\n\nneural-network, mathematical, and acceleration libraries such as cuDNN, cuFFT, cuDSS,\n\n 7\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 9 of 18\n\n\n\ncuSOLVER, cuRAND, CUTLASS, DALI, cuTensor, cuGraph, cuSPARSELt, NPP, NeuralVDB,\n\ncuNumeric, cuCIM, Sionna, cuBLAS, cuSPARSE, NCCL, Thrust, CUB, AmgX, and nvmath-\n\npython. The Accused Products further include low-level CUDA runtime, driver, and system\n\ncomponents, including CUDA, the CUDA Toolkit, CUDA Runtime and Driver components,\n\nCUDA Python, CUDA Quantum, Base Command, GPNVAPI, NVSHMEM, DCGM, Displaced\n\nMicro-Mesh, FLARE, GVDB Voxels, KickstartRT, Mesh Shading, Optical Flow, PTX, SASS,\n\nkernel implementations, firmware, scheduling logic, backend libraries, the CUDA Driver Internal\n\nLayer (CUI), CUDA Driver API, vGPU, GPUDirect, NVML, and other associated runtime, driver,\n\nand sub-component code. The Accused Products further include other Nvidia software, platforms,\n\nand services that implement similar accelerated computing functionality or operate using the same\n\nCUDA-based execution models, architectures, libraries, and runtime components, whether or not\n\nexpressly listed above. The Accused Products also encompass associated and underlying software\n\nlibraries and components that enable or support accelerated execution and any source code or sub-\n\ncomponent code necessary to understand or effect CUDA execution, whether or not separately\n\nanalyzed.\n\n The Accused Products further include (1) any additional products identified in the\n\naccompanying Exhibits 1\u2013599 attached hereto and any later-served amended or supplemental\n\nExhibits; (2) any products that include the same functionality or features described in the Exhibits;\n\nand (3) any prior or subsequent versions of the products identified in the Exhibits that include the\n\nsame features or functionality.\n\n The Accused Products infringe each of the Asserted Patents in a manner fully consistent\n\nwith the Court\u2019s Claim Construction Order (Dkt. 95). For example, as construed, the Accused\n\nProducts implement the claimed \u201caccelerator\u201d as hardware, software, or a combination thereof that\n\nneed not be physically separate from the CPU. The Accused Products likewise perform the claimed\n\n 8\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 10 of 18\n\n\n\nmethod steps in a pipelined and overlapping manner that satisfies the Court\u2019s ordering\n\nrequirements for the asserted claims of the \u2019867 and \u2019438 patents, including parallel execution\n\nwhere permitted and the specific sequencing constraints identified by the Court.\n\n On information and belief, the asserted claim elements charted for one chip architecture\n\nare evidenced by documentation and source code pertaining to the Accused Products for other chip\n\narchitectures, for which the Accused Products have capabilities and functionalities that are\n\nsubstantially the same for the asserted claim elements. Indeed, this is reflected by the different chip\n\narchitectures of the Accused Products sharing materially similar technical specifications and\n\noverlapping documentation as each Accused Product pertains to the accused claim elements.\n\nLikewise, the software implementations analyzed and charted are representative of other related\n\nNvidia software products that rely on the same CUDA-based execution models, libraries, runtime\n\ncomponents, and architectural design choices, and that therefore implement the asserted claim\n\nelements in substantially the same manner such as, for example, performing a math operation or\n\ncomputation in a neural network.\n\n The present infringement contentions also accuse Nvidia\u2019s newly announced Vera CPU\n\nand Rubin GPU products. Neural AI will supplement its infringement contentions as Nvidia\n\nproduces additional information and as these products become commercially available. The\n\npresent infringement contentions further accuse Nvidia\u2019s Jetson hardware products, which, based\n\non information obtained during ongoing fact and expert discovery, infringe one or more Asserted\n\nClaims. Neural AI will supplement its infringement contentions as Nvidia produces additional\n\ninformation regarding these products.\n\n These Final Infringement Contentions are based on public evidence and the limited\n\ndiscovery and source code made available by Nvidia to date, which largely consists of a single\n\nsoftware version for each accused application or library. Nvidia\u2019s has not produced all necessary\n\n 9\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 11 of 18\n\n\n\ntechnical documents or source code sufficient to show the operation of the Accused Products, and\n\nkey categories of technical materials and code remain outstanding. See, e.g., Dkt. 103, 125.\n\nDiscovery and expert analysis are ongoing and include, among other things, the multiple software\n\nversions and builds that may be used in combination, as well as additional libraries and software\n\nfunctions that infringe the asserted claims under the same theories reflected in the claim charts.\n\nThese include, for example, acceleration libraries and functions that infringe the claims in the same\n\nmanner as the cuDNN CTCLoss and RNNForward functions in the two cuDNN source-code\n\nversions produced by Nvidia. Accordingly, Plaintiff expressly reserves the right to amend,\n\nsupplement, or refine these contentions as additional facts are ascertained, discovery is conducted,\n\nanalysis is performed, and research is completed. Plaintiff further reserves the right to amend or\n\nsupplement its Disclosure under the applicable rules and any Court orders, including to reflect\n\nfuture productions by Nvidia.\n\n Defendant\u2019s Infringement. Based upon currently available information, Plaintiff\n\nidentifies the following asserted claims:\n\n \u2022 The \u2019867 Patent. Defendant has infringed and is infringing claims 16-19, literally and/or\n\n under the doctrine of equivalents. Defendant has infringed and is infringing these\n\n claims both directly and indirectly (by inducing infringement pursuant to 35 U.S.C. \u00a7\n\n 271(b) and/or by contributing to infringement pursuant to 35 U.S.C.\u00a7 271(c)).\n\n \u2022 The \u2019461 Patent. Defendant has infringed and is infringing claims 21-25, 27-30,\n\n literally and/or under the doctrine of equivalents. Defendant has infringed and is\n\n infringing these claims both directly and indirectly (by inducing infringement\n\n pursuant to 35 U.S.C. \u00a7 271(b) and/or by contributing to infringement pursuant to 35\n\n U.S.C.\u00a7 271(c)).\n\n \u2022 The \u2019438 Patent. Defendant has infringed and is infringing claims 1, 3-6, 8-9, 12, 14,\n 10\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 12 of 18\n\n\n\n 17-18, 21-23, 29-30, 32, 40, 43-44, 46, 48, 51-52, 55-57, literally and/or under the\n\n doctrine of equivalents. Defendant has infringed and is infringing these claims both\n\n directly and indirectly (by inducing infringement pursuant to 35 U.S.C. \u00a7 271(b) and/or\n\n by contributing to infringement pursuant to 35 U.S.C. \u00a7 271(c)).\n\n Based upon currently available information, Plaintiff asserts that Defendant has infringed\n\nand/or continues to infringe the patents and claims as identified and described in the infringement\n\ncharts for the Accused Products attached as the accompanying Exhibits 1\u2013599 and any later-served\n\namended or supplemental Exhibits. These exhibits contain illustrative examples of Defendant\u2019s\n\npresently known infringement of the Asserted Claims by evidencing the correspondence between\n\n(i) elements of the Asserted Claims and (ii) corresponding structures and/or functions of the\n\nAccused Products. Such examples are illustrative and not exhaustive, additional materials may\n\nevidence infringement, and additional bases of infringement may be present and uncovered during\n\ndiscovery. Plaintiff reserves the right to amend or supplement its Disclosure, including the\n\nattached claim charts, upon Nvidia\u2019s compliance with its discovery obligations.\n\n Each element of each asserted claim is presently alleged to be literally present. However,\n\nto the extent Defendant argues that a limitation is not literally present in the Accused Products, then\n\nDefendant still infringes under the doctrine of equivalents. Any differences alleged to exist\n\nbetween any of the Asserted Claims and any of the Accused Products are insubstantial, and\n\ntherefore each Accused Product also meets each limitation under the doctrine of equivalents, as the\n\nidentified features of the Accused Product perform substantially the same function in substantially\n\nthe same way to achieve substantially the same result as the corresponding claim limitations.\n\nPlaintiff reserves the right to supplement this Disclosure as discovery is conducted, Defendant\n\nprovides any alleged non-infringement positions, and claim construction is completed.\n\n Defendant directly infringes each of the asserted claims under 35 U.S.C. \u00a7271(a) at least\n\n 11\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 13 of 18\n\n\n\nby using, operating, testing, advertising, making, installing, maintaining, distributing, supporting,\n\nproviding instructions for, offering to sell, selling, and/or otherwise providing services including\n\nthe Accused Products\u2014or systems incorporating the Accused Products\u2014within the United States\n\nand/or importing the Accused Products into the United States. Defendant also directly infringes\n\neach of the claims at least by performing, or being responsible for the performance of (e.g., the\n\nacts are attributable to it), each of the claimed steps as set forth in the accompanying charts.\n\nDefendant\u2019s acts of direct infringement are further set forth in the accompanying Exhibits and any\n\nlater-served amended or supplemental Exhibits.\n\n Defendant also indirectly infringes the Asserted Claims by inducing infringement pursuant\n\nto 35 U.S.C. \u00a7 271(b)). Defendant has had knowledge of each of the asserted patents and of the\n\nspecific manner by which the Accused Products infringe each patent since at least September 2024,\n\nwhen Plaintiff filed and served its original complaint. Defendant knowingly induced one or more\n\nthird parties (e.g., business partners, customers, or others), to infringe the Asserted Claims by\n\nmaking the Accused Products available on Defendant\u2019s website, widely advertising the Accused\n\nProducts, providing applications that allow partners and users to access the Accused Products,\n\nproviding instructions for installing the Accused Products, and providing technical support to users\n\nand/or engaging in activities that aid and abet infringement of the Asserted Patents by end users\n\nwithin the United States, with knowledge and intent that performance of such actions would\n\ninfringe the Asserted Claims. Defendant committed these acts with knowledge or willful blindness\n\nthat such induced acts would constitute infringement of the Asserted Claims at least as of the filing\n\nof the original complaint. Defendant also has had actual or constructive notice of the technology\n\nclaimed in the Asserted Patents since at least 2007, when the inventors of the Asserted Patents first\n\ndiscussed their patented technologies with Mr. Sanford Russell, then the CTO of Nvidia. In\n\naddition, the inventors of the Asserted Patents held multiple discussions with Nvidia regarding a\n\n 12\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 14 of 18\n\n\n\npotential investment in or acquisition of their company, Neurala, Inc., and its assets, including the\n\npatent family that includes the Asserted Patents. Defendant knew or should have known that it\n\ninfringed the Asserted Patents based on its knowledge of the same. Alternatively or additionally,\n\nDefendant was willfully blind to the fact that it infringed the Asserted Patents despite its\n\nknowledge of the same, based on, for example, Defendant\u2019s having cited the application for the\n\n\u2019867 Patent on the face of its own patent since at least June 28, 2010, see Nvidia U.S. Patent No.\n\n8,922,566, and the similarity of the Accused Products to Plaintiff\u2019s patented technology.\n\nAdditional evidence of Defendant\u2019s inducement of infringement by others is set forth in each of\n\naccompanying Exhibits.\n\n Defendant also indirectly infringes the Asserted Claims by contributing to infringement\n\npursuant to 35 U.S.C. \u00a7 271(c). Each of the Accused Products is a material part of the claims, and\n\nDefendant knew each of the Accused Products is especially made or especially adapted for use in\n\nan infringement of the Asserted Claims. Further, the Accused Products have no substantial non-\n\ninfringing uses, as set forth in the example claim charts.\n\n Defendant also contributes to infringement by its customers and end users of the Accused\n\nProducts by offering to sell or selling within the United States or importing into the United States\n\nthe Accused Products, which are for use in practicing, and under normal operation practice,\n\nmethods claimed in the Asserted Patents, constituting a material part of the inventions claimed,\n\nand not a staple article or commodity of commerce suitable for substantial non-infringing use.\n\nIndeed, the Accused Products and the exemplary functionality identified in the accompanying\n\nExhibits have no substantial non-infringing uses but instead are specifically designed to practice\n\nthe Asserted Patents. Additional evidence of Defendant\u2019s contributory infringement is set forth in\n\neach of the Exhibits and any later-served amended or supplemental Exhibits.\n\n Priority Dates. Plaintiff presently identifies the following priority dates for the Asserted\n\n 13\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 15 of 18\n\n\n\nPatents:\n\n \u2022 All Asserted Claims of the \u2019867 Patent are entitled to a priority date corresponding\n\n to the conception of the claimed inventions, which occurred no later than February\n\n 25, 2005. The conception of the inventions claimed in the \u2019867 Patent was followed\n\n by continuous diligence and actual reduction to practice of the claimed inventions\n\n no later than December 14, 2005. Following the actual reduction to practice of the\n\n claimed invention, there was constructive reduction to practice corresponding to\n\n the filing of U.S. Provisional Application No. 60/826,892 on September 25, 2006.\n\n See NAI_0007731-NAI_0007923.\n\n \u2022 All Asserted Claims of the \u2019461 Patent are entitled to a priority date corresponding\n\n to the conception of the claimed inventions, which occurred no later than February\n\n 25, 2005. The conception of the inventions claimed in the \u2019461 Patent was followed\n\n by continuous diligence and actual reduction to practice of the claimed inventions\n\n no later than December 14, 2005. Following the actual reduction to practice of the\n\n claimed inventions, there was constructive reduction to practice corresponding to\n\n the filing of U.S. Provisional Application No. 60/826,892 on September 25, 2006.\n\n See NAI_0007731-NAI_0007923.\n\n \u2022 All Asserted Claims of the \u2019438 Patent are entitled to a priority date corresponding\n\n to the conception of the claimed inventions, which occurred no later than February\n\n 25, 2005. The conception of the inventions claimed in the \u2019438 Patent was followed\n\n by continuous diligence and actual reduction to practice of the claimed inventions\n\n no later than December 14, 2005. Following the actual reduction to practice of the\n\n claimed inventions, there was constructive reduction to practice corresponding to\n\n the filing of U.S. Provisional Application No. 60/826,892 on September 25, 2006.\n\n 14\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 16 of 18\n\n\n\n See NAI_0007731-NAI_0007923.\n\n Plaintiff\u2019s investigation and analysis is ongoing, and Plaintiff reserves the right to assert and\n\nrely on an earlier invention date in the event Defendant identifies alleged prior art that dated earlier\n\nthan the identified priority date corresponding to a date of conception followed by diligence and\n\nreduction to practice of the claimed inventions.\n\n\n\n DATED: January 20, 2026 Respectfully submitted,\n\n /s/ Tanner Laiche\n Max L. Tribble\n Texas State Bar 20213950\n Brian D. Melton\n Texas State Bar 24010620\n Rocco Magni\n Texas State Bar 24092745\n Samuel Drezdzon\n Texas State Bar 24117374\n SUSMAN GODFREY L.L.P.\n 1000 Louisiana\n Suite 5100\n Houston, TX 77002\n Telephone: (713) 651-9366\n Facsimile: (713) 654-6666\n mtribble@susmangodfrey.com\n bmelton@susmangodfrey.com\n rmagni@susmangodfrey.com\n sdrezdzon@susmangodfrey.com\n\n Tamar Lusztig\n NY State Bar 5125174\n Emily Portuguese\n NY State Bar 5920327\n One Manhattan West, 50th Floor\n New York, NY 10001\n tlusztig@susmangodfrey.com\n eportuguese@susmangodfrey.com\n\n Tanner Laiche\n WA State Bar 60450\n 401 Union Street, Suite 3000\n Seattle, WA 98101\n tlaiche@susmangodfrey.com\n 15\n\fCase 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 17 of 18\n\n\n\n\n Mark D. Siegmund\n Texas State Bar No. 24117055\n CHERRY JOHSON SIEGMUND\n JAMES PC\n Bridgeview Center\n 7901 Fish Pond Road, 2nd Floor\n Waco, Texas 76710\n msiegmund@cjsjlaw.com\n\n Max Ciccarelli\n Texas State Bar No. 00787242\n CICCARELLI LAW FIRM LLC\n 100 N. 6th Street, Suite 502\n Waco, Texas 76701\n Max@CiccarelliLawFirm.com\n\n Attorneys for Plaintiff Neural AI, LLC\n\n\n\n\n 16\n\f Case 7:26-mc-00324-DC Document 1-8 Filed 08/18/26 Page 18 of 18\n\n\n\n\n CERTIFICATE OF SERVICE\n\n The undersigned hereby certifies that a true and correct copy of the foregoing document has\n\nbeen served on January 20, 2026 to all counsel of record via electronic mail.\n\n\n\n /s/ Tanner Laiche\n Tanner Laiche\n\n\n\n\n 17\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:21.725089-07:00","document_number":"1","attachment_number":8,"pacer_doc_id":"181037219903","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 7","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514522/","id":490514522,"tags":[],"absolute_url":"/docket/74667129/1/9/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.078488-07:00","date_modified":"2026-08-23T02:34:06.360316-07:00","sha1":"e62bc678fbacf83a1e97fce34c4ec0c8b82b264e","page_count":47,"file_size":458373,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.9.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.9.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-9 Filed 08/18/26 Page 1 of 47\n\n\n\n\n EXHIBIT\n\n 8\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 2 of147\n of 46\n\n\n\n\n IN THE UNITED STATES DISTRICT COURT\n FOR THE WESTERN DISTRICT OF TEXAS\n PUBLIC VERSION\nNEURAL AI, LLC\n Civil Action No. 7:24-cv-00221\n Plaintiff,\n\n v. JURY TRIAL DEMANDED\n\nNVIDIA CORPORATION.,\n\n Defendant.\n\n\n DEFENDANT\u2019S AMENDED ANSWER TO PLAINTIFF\u2019S AMENDED COMPLAINT\n\n Defendant NVIDIA Corporation (\u201cNVIDIA\u201d) hereby provides its amended answer to\n\nPlaintiff Neural AI, LLC\u2019s (\u201cPlaintiff\u201d) Amended Complaint for Patent Infringement (Dkt. 30)\n\n(\u201cComplaint\u201d). The headings and subheadings in Defendant\u2019s Answer are used solely for purposes\n\nof convenience and organization to mirror those appearing in the Complaint; to the extent that any\n\nheadings or other non-numbered statements in the Complaint contain or imply any allegations,\n\nDefendant denies each and every allegation therein. Except as expressly admitted, all allegations\n\nin the Complaint are denied.\n\n 1. Defendant admits that graphics processor units may be used for artificial\n\nintelligence, machine learning, or complex numerical simulation applications. Defendant admits\n\nthat GPU computing powers many of the most advanced and powerful forms of artificial\n\nintelligence over the past decade. Defendant denies the remaining allegations of Paragraph 1.\n\n 2. Defendant admits that graphics processor units may be used for complex numerical\n\nsimulation, machine learning, and training complex models. Defendant further admits that\n\ngraphics processor units typically have more computational processors than central processing\n\nunits and are capable of parallel processing. Defendant does not have knowledge or information\n\n\n\n\n 1\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 3 of247\n of 46\n\n\n\n\nsufficient to form a belief as to the truth of the remaining allegations contained in Paragraph 2 and\n\non that basis denies them.\n\n 3. Defendant denies the allegations in Paragraph 3 of the Complaint.\n\n 4. Defendant denies the allegations in Paragraph 4 of the Complaint.\n\n NATURE OF THE CASE\n\n 5. Defendant admits that Plaintiff has asserted claims for patent infringement arising\n\nunder 35 U.S.C. \u00a7 1, et seq., but denies all of Plaintiff\u2019s allegations of infringement. Except as\n\nexpressly admitted, Defendant denies the remaining allegations in Paragraph 5 of the Complaint.\n\n 6. Defendant does not have knowledge or information sufficient to form a belief as to\n\nthe truth of the allegations contained in Paragraph 6 and on that basis denies them.\n\n 7. Defendant does not have knowledge or information sufficient to form a belief as to\n\nthe truth of the allegations contained in Paragraph 7 and on that basis denies them.\n\n 8. Defendant does not have knowledge or information sufficient to form a belief as to\n\nthe truth of the allegations contained in Paragraph 8 and on that basis denies them.\n\n 9. Defendant admits that Defendant is a Delaware corporation with its headquarters\n\nin Santa Clara, California. Defendant further admits that it is registered to conduct business in\n\nTexas. Defendant further admits that it has an office in Austin, Texas. Except as expressly\n\nadmitted, Defendant denies the remaining allegations in Paragraph 9 of the Complaint.\n\n JURISDICTION & VENUE\n\n 10. Defendant admits that Plaintiff purports to assert claims for patent infringement\n\narising under 35 U.S.C. \u00a7 1, et seq., but denies all claims of infringement by Defendant. Defendant\n\nadmits that the Court has subject matter jurisdiction pursuant to 28 U.S.C. \u00a7\u00a7 1331 and 1338(a).\n\n\n\n\n 2\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 4 of347\n of 46\n\n\n\n\nExcept as expressly admitted, Defendant denies the remaining allegations in Paragraph 10 of the\n\nComplaint.\n\n 11. Defendant admits that this Court has personal jurisdiction for the purpose of this\n\nparticular action and that it does business in Texas and in this District. Except as expressly\n\nadmitted, Defendant denies the remaining allegations in Paragraph 11 of the Complaint.\n\n 12. Defendant admits that Defendant has conducted business in within this District, but\n\ndenies all allegations of infringement. Except as expressly admitted, Defendant denies the\n\nremaining allegations in Paragraph 12 of the Complaint.\n\n 13. Defendant admits that this Court has personal jurisdiction for the purpose of this\n\nparticular action. To the extent the allegations of Paragraph 13 purport to quote from or\n\ncharacterize the contents of written documents, those documents speak for themselves. Defendant\n\ndenies the remaining allegations in Paragraph 13 of the complaint.\n\n 14. Defendant admits that venue is proper for this case but denies that it is a convenient\n\nforum for NVIDIA and its witnesses. Except as expressly admitted, Defendant denies the\n\nremaining allegations in Paragraph 14 of the complaint.\n\n 15. Defendant Nvidia Corporation is a registered business in Texas and has regular and\n\nestablished places of business Defendant admits that it is a registered business in Texas and\n\nmaintains an office located at 11001 Lakeline Blvd, Suite 100 Bldg. 2, Austin, Texas 78717. To\n\nthe extent the allegations of Paragraph 15 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 15 of the complaint.\n\n\n\n\n 3\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 5 of447\n of 46\n\n\n\n\n 16. Defendant admits that it has hundreds of employees in this District. Defendant does\n\nnot have knowledge or information sufficient to form a belief as to the truth of the remaining\n\nallegations contained in Paragraph 16 and on that basis denies them.\n\n 17. Defendant admits that it has open job postings for jobs that may be filled in a\n\nnumber of locations, including in this District. Defendant does not have knowledge or information\n\nsufficient to form a belief as to the truth of the remaining allegations contained in Paragraph 17\n\nand on that basis denies them.\n\n 18. Defendant admits that it engages it engages in business in this District. Defendant\n\nadmits that it has customer-facing personnel and operations in this District. Defendant admits that\n\nit provides technical support to partners and customers for its products in this District. Except as\n\nexpressly admitted, Defendant denies the remaining allegations in Paragraph 18 of the Complaint.\n\n 19. Defendant denies the allegations in Paragraph 19 of the Complaint.\n\n 20. Defendant admits that it sells products and provides services in the State of Texas,\n\nbut denies that those products or services infringe the Asserted Patents. To the extent the\n\nallegations in Paragraph 20 of the Complaint relate to the knowledge or actions of third parties,\n\nDefendant does not have knowledge or information sufficient to form a belief as to the truth of\n\nthose allegations and on that basis denies them. Except as expressly admitted, Defendant denies\n\nthe remaining allegations in Paragraph 20 of the Complaint.\n\n 21. Defendant admits that it sells products and provides services in the State of Texas,\n\nbut denies that the use of those products or services infringes the Asserted Patents. To the extent\n\nthe allegations in Paragraph 21 of the Complaint relate to the knowledge or actions of third parties,\n\nDefendant does not have knowledge or information sufficient to form a belief as to the truth of\n\n\n\n\n 4\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 6 of547\n of 46\n\n\n\n\nthose allegations and on that basis denies them. Except as expressly admitted, Defendant denies\n\nthe remaining allegations in Paragraph 21 of the Complaint.\n\n 22. Defendant admits that it partners with resellers and managed service providers for\n\nthe sale or installation of certain NVIDIA products. To the extent the allegations of Paragraph 22\n\npurport to quote from or characterize the contents of websites, those documents speak for\n\nthemselves. Except as expressly admitted, Defendant denies the remaining allegations in\n\nParagraph 22 of the Complaint.\n\n 23. Defendant admits that it partners with data center providers. To the extent the\n\nallegations of Paragraph 23 purport to quote from or characterize the contents of written\n\ndocuments, those documents speak for themselves. To the extent the allegations in Paragraph 23\n\nof the Complaint relate to the knowledge or actions of third parties, Defendant does not have\n\nknowledge or information sufficient to form a belief as to the truth of those allegations and on that\n\nbasis denies them. Except as expressly admitted, Defendant denies the remaining allegations in\n\nParagraph 23 of the Complaint.\n\n 24. Defendant denies the allegations in Paragraph 24 of the Complaint.\n\n 25. To the extent the allegations of Paragraph 25 purport to quote from or characterize\n\nthe contents of websites, those websites speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 25 of the Complaint.\n\n 26. To the extent the allegations of Paragraph 26 purport to quote from or characterize\n\nthe contents of websites, those websites speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 26 of the Complaint.\n\n\n\n\n 5\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 7 of647\n of 46\n\n\n\n\n 27. To the extent the allegations of Paragraph 27 purport to quote from or characterize\n\nthe contents of websites, those websites speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 27 of the Complaint.\n\n 28. Defendant denies the allegations in Paragraph 28 of the Complaint.\n\n 29. To the extent the allegations of Paragraph 29 purport to quote from or characterize\n\nthe contents of written documents, those documents speak for themselves. Defendant denies the\n\nremaining allegations in Paragraph 29 of the Complaint.\n\n 30. Defendant denies the allegations in Paragraph 30 of the Complaint.\n\n PLAINTIFF\u2019S PATENTED INNOVATIONS\n\n 31. Defendant does not have knowledge or information sufficient to form a belief as to\n\nthe truth of the allegations contained in Paragraph 31 and on that basis denies them.\n\n The GPU-Based Acceleration Patents\n U.S. Patent Nos. 8,648,867, RE49,461, and RE48,438\n\n 32. Defendant admits that the \u2019461 Patent purports to be a continuation of the \u2019438\n\nPatent, which purports to be an application for reissue of U.S. Patent No. 9,189,828, which purports\n\nto be a continuation of the \u2019867 Patent. Except as expressly admitted, Defendant denies the\n\nremaining allegations in Paragraph 32 of the Complaint.\n\n 33. Defendant admits that Exhibit 1 to the Complaint appears to be a copy of the \u2019867\n\nPatent, which is titled \u201cGraphic Processor Based Accelerator System and Method,\u201d was filed on\n\nSeptember 24, 2007, and was issued on February 11, 2014. Defendant further admits that the \u2019867\n\nPatent purports to claim priority to U.S. Provisional App. No. 60/826,892 but denies that the \u2019867\n\nPatent is entitled to that claim of priority. Except as expressly admitted, Defendant denies the\n\nremaining allegations in Paragraph 33 of the Complaint.\n\n\n\n\n 6\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 8 of747\n of 46\n\n\n\n\n 34. Defendant admits that Exhibit 2 to the Complaint appears to be a copy of the \u2019438\n\nPatent, which is titled \u201cGraphic Processor Based Accelerator System and Method,\u201d was filed on\n\nNovember 9, 2017, and was issued on February 16, 2021. Defendant further admits that the \u2019438\n\nPatent purports to claim priority to U.S. Provisional App. No. 60/826,892 but denies that the \u2019438\n\nPatent is entitled to that claim of priority. Except as expressly admitted, Defendant denies the\n\nremaining allegations in Paragraph 34 of the Complaint.\n\n 35. Defendant admits that Exhibit 3 to the Complaint appears to be a copy of the \u2019461\n\nPatent, which is titled \u201cGraphic Processor Based Accelerator System and Method,\u201d was filed on\n\nDecember 29, 2020, and was issued on March 14, 2023. Defendant further admits that the \u2019461\n\nPatent purports to claim priority to U.S. Provisional App. No. 60/826,892 but denies that the \u2019461\n\nPatent is entitled to that claim of priority. Except as expressly admitted, Defendant denies the\n\nremaining allegations in Paragraph 35 of the Complaint.\n\n 36. To the extent the allegations of Paragraph 36 purport to quote from or characterize\n\nthe contents of the \u2019867 Patent, that document speaks for itself. Defendant denies the remaining\n\nallegations in Paragraph 36 of the Complaint.\n\n 37. To the extent the allegations of Paragraph 37 purport to quote from or characterize\n\nthe contents of the \u2019867 Patent, that document speaks for itself. Defendant denies the remaining\n\nallegations in Paragraph 37 of the Complaint.\n\n 38. To the extent the allegations of Paragraph 38 purport to quote from or characterize\n\nthe contents of the \u2019867 Patent, that document speaks for itself. Defendant denies the remaining\n\nallegations in Paragraph 38 of the Complaint.\n\n\n\n\n 7\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 9 of847\n of 46\n\n\n\n\n 39. To the extent the allegations of Paragraph 39 purport to quote from or characterize\n\nthe contents of the \u2019461 and \u2019438 Patents, those documents speak for themselves. Defendant denies\n\nthe remaining allegations in Paragraph 39 of the Complaint.\n\n 40. To the extent the allegations of Paragraph 40 purport to quote from or characterize\n\nthe contents of the Asserted Patents, those documents speak for themselves. Defendant denies the\n\nremaining allegations in Paragraph 40 of the Complaint.\n\n ACCUSED PRODUCTS\n\n 41. Defendant admits that it offers GPUs and various hardware and software products,\n\nbut specifically denies that those products infringe the Asserted Patents. To the extent the\n\nallegations of Paragraph 41 purport to quote from or characterize the contents of websites, those\n\ndocuments speak for themselves. Except as expressly admitted, Defendant denies the remaining\n\nallegations in Paragraph 41 of the Complaint.\n\n 42. Defendant admits that \u201cHopper,\u201d \u201cAda Lovelace,\u201d \u201cAmpere,\u201d \u201cTuring,\u201d \u201cVolta,\u201d\n\n\u201cPascal,\u201d and \u201cMaxwell\u201d are architectures of Defendant\u2019s GPUs but specifically denies that those\n\nproducts infringe the Asserted Patents. To the extent the allegations of Paragraph 42 purport to\n\nquote from or characterize the contents of websites, those documents speak for themselves. Except\n\nas expressly admitted, Defendant denies the remaining allegations in Paragraph 42 of the\n\nComplaint.\n\n 43. Defendant admits that its products include the H100 and H200 GPUs, but\n\nspecifically denies that those products infringe the Asserted Patents. Defendant further admits that\n\nit offers the GH200 \u201cGrace Hopper Superchip,\u201d but likewise specifically denies that this product\n\ninfringes the Asserted Patents. To the extent the allegations of Paragraph 43 purport to quote from\n\n\n\n\n 8\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9 130FiledFiled\n 08/18/26\n 11/25/25Page\n Page\n 10 of9 47\n of 46\n\n\n\n\nor characterize the contents of websites, those documents speak for themselves. Except as\n\nexpressly admitted, Defendant denies the remaining allegations in Paragraph 43 of the Complaint.\n\n 44. Defendant admits that its products include GPUs with the Ada Lovelace\n\narchitecture, but specifically denies that those products infringe the Asserted Patents. To the extent\n\nthe allegations of Paragraph 44 purport to quote from or characterize the contents of websites,\n\nthose documents speak for themselves. Except as expressly admitted, Defendant denies the\n\nremaining allegations in Paragraph 44 of the Complaint.\n\n 45. Defendant admits that its products include GPUs with the Ampere architecture, but\n\nspecifically denies that those products infringe the Asserted Patents. To the extent the allegations\n\nof Paragraph 45 purport to quote from or characterize the contents of websites, those documents\n\nspeak for themselves. Except as expressly admitted, Defendant denies the remaining allegations\n\nin Paragraph 45 of the Complaint.\n\n 46. Defendant admits that its products include GPUs with the Turing architecture, but\n\nspecifically denies that those products infringe the Asserted Patents. To the extent the allegations\n\nof Paragraph 46 purport to quote from or characterize the contents of websites, those documents\n\nspeak for themselves. Except as expressly admitted, Defendant denies the remaining allegations\n\nin Paragraph 46 of the Complaint.\n\n 47. Defendant admits that its products include GPUs with the Volta architecture, but\n\nspecifically denies that those products infringe the Asserted Patents. To the extent the allegations\n\nof Paragraph 47 purport to quote from or characterize the contents of websites, those documents\n\nspeak for themselves. Except as expressly admitted, Defendant denies the remaining allegations\n\nin Paragraph 47 of the Complaint.\n\n\n\n\n 9\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 11 of\n 1047\n of 46\n\n\n\n\n 48. Defendant admits that its products include GPUs with the Pascal architecture, but\n\nspecifically denies that those products infringe the Asserted Patents. To the extent the allegations\n\nof Paragraph 48 purport to quote from or characterize the contents of websites, those documents\n\nspeak for themselves. Except as expressly admitted, Defendant denies the remaining allegations\n\nin Paragraph 48 of the Complaint.\n\n 49. Defendant admits that its products include GPUs with the Maxwell architecture,\n\nbut specifically denies that those products infringe the Asserted Patents. To the extent the\n\nallegations of Paragraph 49 purport to quote from or characterize the contents of websites, those\n\ndocuments speak for themselves. Except as expressly admitted, Defendant denies the remaining\n\nallegations in Paragraph 49 of the Complaint.\n\n 50. Defendant admits that certain of Defendant\u2019s GPU architectures support the CUDA\n\nplatform. To the extent the allegations of Paragraph 50 purport to quote from or characterize the\n\ncontents of websites, those documents speak for themselves. Except as expressly admitted,\n\nDefendant denies the remaining allegations in Paragraph 50 of the Complaint.\n\n 51. Defendant admits that it has marketed products under the EGX, HGX, DGX, and\n\nOVX product names, but specifically denies that those products infringe the Asserted Patents. To\n\nthe extent the allegations of Paragraph 51 purport to quote from or characterize the contents of\n\nwebsites, those documents speak for themselves. Except as expressly admitted, Defendant denies\n\nthe remaining allegations in Paragraph 51 of the Complaint.\n\n 52. To the extent the allegations of Paragraph 52 purport to quote from or characterize\n\nthe contents of websites, those documents speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 52 of the Complaint.\n\n\n\n\n 10\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 12 of\n 1147\n of 46\n\n\n\n\n 53. Paragraph 53 of the Complaint does not contain any allegation which requires a\n\nresponse.\n\n 54. To the extent the allegations of Paragraph 54 purport to quote from or characterize\n\nthe contents of websites, those documents speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 54 of the Complaint.\n\n 55. To the extent the allegations of Paragraph 55 purport to quote from or characterize\n\nthe contents of websites, those documents speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 55 of the Complaint.\n\n 56. To the extent the allegations of Paragraph 56 purport to quote from or characterize\n\nthe contents of websites, those documents speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 56 of the Complaint.\n\n 57. To the extent the allegations of Paragraph 57 purport to quote from or characterize\n\nthe contents of websites, those documents speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 57 of the Complaint.\n\n 58. To the extent the allegations of Paragraph 58 purport to quote from or characterize\n\nthe contents of websites, those documents speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 58 of the Complaint.\n\n 59. To the extent the allegations of Paragraph 59 purport to quote from or characterize\n\nthe contents of websites, those documents speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 59 of the Complaint.\n\n 60. To the extent the allegations of Paragraph 60 purport to quote from or characterize\n\nthe contents of websites, those documents speak for themselves. Defendant denies the remaining\n\nallegations in Paragraph 60 of the Complaint.\n\n\n\n\n 11\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 13 of\n 1247\n of 46\n\n\n\n\n FIRST CAUSE OF ACTION\n (INFRINGEMENT OF THE \u2019867 PATENT)\n\n 61. Defendant restates and incorporates by reference its answers to the preceding\n\nparagraphs of the Complaint.\n\n 62. Defendant denies the allegations in Paragraph 62 of the Complaint.\n\n 63. Paragraph 63 of the Complaint does not contain any allegation which requires a\n\nresponse.\n\n 64. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 64 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 64 of the Complaint.\n\n 65. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 65 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 65 of the Complaint.\n\n 66. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 66 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 66 of the Complaint.\n\n 67. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 67 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 67 of the Complaint.\n\n\n\n\n 12\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 14 of\n 1347\n of 46\n\n\n\n\n 68. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 68 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 68 of the Complaint.\n\n 69. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 69 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 69 of the Complaint.\n\n 70. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 70 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 70 of the Complaint.\n\n 71. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 71 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 71 of the Complaint.\n\n 72. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 72 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 72 of the Complaint.\n\n 73. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 73 purport to quote from or characterize the contents of\n\n\n\n\n 13\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 15 of\n 1447\n of 46\n\n\n\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 73 of the Complaint.\n\n 74. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 74 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 74 of the Complaint.\n\n 75. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 75 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 75 of the Complaint.\n\n 76. Defendant denies the allegations in Paragraph 76 of the Complaint.\n\n 77. Defendant admits that Mr. Sanford Russell was employed by NVIDIA in 2007.\n\nDefendant denies that Mr. Russell was, at any point in time, the CTO of NVIDIA. Defendant does\n\nnot have knowledge or information sufficient to form a belief as to the truth of the allegations\n\nregarding the alleged communications between NVIDIA employees and Neurala made in 2007\n\nand on that basis denies them. Except as expressly admitted, Defendant denies the remaining\n\nallegations in Paragraph 77 of the Complaint.\n\n 78. Defendant admits that, in or around 2016, Defendant had discussions with Neurala,\n\nInc. and that at least Mr. Alvin Lin and/or Mr. Jeff Herbst from Defendant were involved.\n\nDefendant also admits that, in 2016, Defendant had discussions with at least one of the inventors\n\nregarding potential investments in Neurala, Inc. Defendant denies the remaining allegations in\n\nParagraph 78 of the Complaint.\n\n\n\n\n 14\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 16 of\n 1547\n of 46\n\n\n\n\n 79. Defendant admits that it hosted its GPU Technology Conference in May of 2017.\n\nTo the extent the allegations of Paragraph 79 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 79 of the Complaint.\n\n 80. Defendant denies the allegations in Paragraph 80 of the Complaint.\n\n 81. Defendant denies the allegations in Paragraph 81 of the Complaint.\n\n 82. Defendant denies the allegations in Paragraph 82 of the Complaint.\n\n 83. Defendant denies the allegations in Paragraph 83 of the Complaint.\n\n 84. Defendant denies the allegations in Paragraph 84 of the Complaint.\n\n 85. Defendant denies the allegations in Paragraph 85 of the Complaint.\n\n 86. Defendant denies the allegations in Paragraph 86 of the Complaint.\n\n 87. Defendant admits that it sells and has sold its products and provides certain\n\ntechnical support to its customers for those products. To the extent the allegations of Paragraph\n\n87 purport to quote from or characterize the contents of websites, those websites speak for\n\nthemselves. Defendant denies the remaining allegations in Paragraph 87 of the Complaint.\n\n 88. Defendant denies the allegations in Paragraph 88 of the Complaint.\n\n 89. Defendant denies the allegations in Paragraph 89 of the Complaint.\n\n 90. Defendant denies the allegations in Paragraph 90 of the Complaint.\n\n 91. Defendant denies the allegations in Paragraph 91 of the Complaint.\n\n 92. Defendant denies the allegations in Paragraph 92 of the Complaint.\n\n 93. Defendant denies the allegations in Paragraph 93 of the Complaint.\n\n\n\n\n 15\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 17 of\n 1647\n of 46\n\n\n\n\n SECOND CAUSE OF ACTION\n (INFRINGEMENT OF THE \u2019438 PATENT)\n\n 94. Defendant restates and incorporates by reference its answers to the preceding\n\nparagraphs of the Complaint.\n\n 95. Defendant denies the allegations in Paragraph 95 of the Complaint.\n\n 96. Paragraph 96 of the Complaint does not contain any allegation which requires a\n\nresponse.\n\n 97. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 97 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 97 of the Complaint.\n\n 98. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 98 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 98 of the Complaint.\n\n 99. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 99 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 99 of the Complaint.\n\n 100. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 100 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 100 of the Complaint.\n\n\n\n\n 16\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 18 of\n 1747\n of 46\n\n\n\n\n 101. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 101 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 101 of the Complaint.\n\n 102. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 102 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 102 of the Complaint.\n\n 103. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 103 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 103 of the Complaint.\n\n 104. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 104 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 104 of the Complaint.\n\n 105. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 105 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 105 of the Complaint.\n\n 106. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 106 purport to quote from or characterize the contents of\n\n\n\n\n 17\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 19 of\n 1847\n of 46\n\n\n\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 106 of the Complaint.\n\n 107. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 107 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 107 of the Complaint.\n\n 108. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 108 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 108 of the Complaint.\n\n 109. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 109 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 109 of the Complaint.\n\n 110. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 110 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 110 of the Complaint.\n\n 111. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 111 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 111 of the Complaint.\n\n\n\n\n 18\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 20 of\n 1947\n of 46\n\n\n\n\n 112. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 112 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 112 of the Complaint.\n\n 113. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 113 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 113 of the Complaint.\n\n 114. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 114 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 114 of the Complaint.\n\n 115. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 115 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 115 of the Complaint.\n\n 116. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 116 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 116 of the Complaint.\n\n 117. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 117 purport to quote from or characterize the contents of\n\n\n\n\n 19\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 21 of\n 2047\n of 46\n\n\n\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 117 of the Complaint.\n\n 118. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 118 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 118 of the Complaint.\n\n 119. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 119 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 119 of the Complaint.\n\n 120. Defendant denies the allegations in Paragraph 120 of the Complaint.\n\n 121. Defendant admits that Mr. Sanford Russell was employed by NVIDIA in 2007.\n\nDefendant denies that Mr. Russell was, at any point in time, the CTO of NVIDIA. Defendant does\n\nnot have knowledge or information sufficient to form a belief as to the truth of the allegations\n\nregarding the alleged communications between NVIDIA employees and Neurala made in 2007\n\nand on that basis denies them. Defendant admits that it became aware of the \u2019438 Patent since at\n\nleast the filing of this Complaint. Except as expressly admitted, Defendant denies the remaining\n\nallegations in Paragraph 121 of the Complaint.\n\n 122. Defendant admits that, in or around 2016, Defendant had discussions with Neurala,\n\nInc. and that at least Mr. Alvin Lin and/or Mr. Jeff Herbst from Defendant were involved.\n\nDefendant also admits that, in 2016, Defendant had discussions with at least one of the inventors\n\nregarding potential investments in Neurala, Inc. Defendant denies the remaining allegations in\n\nParagraph 122 of the Complaint.\n\n\n\n\n 20\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 22 of\n 2147\n of 46\n\n\n\n\n 123. Defendant admits that it hosted its GPU Technology Conference in May of 2017.\n\nTo the extent the allegations of Paragraph 123 purport to quote from or characterize the contents\n\nof websites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 123 of the Complaint.\n\n 124. Defendant denies the allegations in Paragraph 124 of the Complaint.\n\n 125. Defendant denies the allegations in Paragraph 125 of the Complaint.\n\n 126. Defendant denies the allegations in Paragraph 126 of the Complaint.\n\n 127. Defendant denies the allegations in Paragraph 127 of the Complaint.\n\n 128. Defendant denies the allegations in Paragraph 128 of the Complaint.\n\n 129. Defendant denies the allegations in Paragraph 129 of the Complaint.\n\n 130. Defendant denies the allegations in Paragraph 130 of the Complaint.\n\n 131. Defendant admits that it sells and has sold its products and provides certain\n\ntechnical support to its customers for those products. To the extent the allegations of Paragraph\n\n131 purport to quote from or characterize the contents of websites, those websites speak for\n\nthemselves. Defendant denies the remaining allegations in Paragraph 131 of the Complaint.\n\n 132. Defendant denies the allegations in Paragraph 132 of the Complaint.\n\n 133. Defendant denies the allegations in Paragraph 133 of the Complaint.\n\n 134. Defendant denies the allegations in Paragraph 134 of the Complaint.\n\n 135. Defendant denies the allegations in Paragraph 135 of the Complaint.\n\n 136. Defendant denies the allegations in Paragraph 136 of the Complaint.\n\n 137. Defendant denies the allegations in Paragraph 137 of the Complaint.\n\n\n\n\n 21\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 23 of\n 2247\n of 46\n\n\n\n\n THIRD CAUSE OF ACTION\n (INFRINGEMENT OF THE \u2019461 PATENT)\n\n 138. Defendant restates and incorporates by reference its answers to the preceding\n\nparagraphs of the Complaint.\n\n 139. Defendant denies the allegations in Paragraph 139 of the Complaint.\n\n 140. Paragraph 140 of the Complaint does not contain any allegation which requires a\n\nresponse.\n\n 141. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 141 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 141 of the Complaint.\n\n 142. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 142 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 142 of the Complaint.\n\n 143. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 143 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 143 of the Complaint.\n\n 144. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 144 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 144 of the Complaint.\n\n\n\n\n 22\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 24 of\n 2347\n of 46\n\n\n\n\n 145. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 145 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 145 of the Complaint.\n\n 146. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 146 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 146 of the Complaint.\n\n 147. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 147 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 147 of the Complaint.\n\n 148. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 148 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 148 of the Complaint.\n\n 149. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 149 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 149 of the Complaint.\n\n 150. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 150 purport to quote from or characterize the contents of\n\n\n\n\n 23\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 25 of\n 2447\n of 46\n\n\n\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 150 of the Complaint.\n\n 151. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 151 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 151 of the Complaint.\n\n 152. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 152 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 152 of the Complaint.\n\n 153. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 153 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 153 of the Complaint.\n\n 154. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 154 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 154 of the Complaint.\n\n 155. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 155 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 155 of the Complaint.\n\n\n\n\n 24\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 26 of\n 2547\n of 46\n\n\n\n\n 156. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 156 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 156 of the Complaint.\n\n 157. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 157 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 157 of the Complaint.\n\n 158. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 158 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 158 of the Complaint.\n\n 159. Defendant specifically denies that it has infringed any of the Asserted Patents. To\n\nthe extent the allegations of Paragraph 159 purport to quote from or characterize the contents of\n\nwebsites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 159 of the Complaint.\n\n 160. Defendant denies the allegations in Paragraph 160 of the Complaint.\n\n 161. Defendant admits that Mr. Sanford Russell was employed by NVIDIA in 2007.\n\nDefendant denies that Mr. Russell was, at any point in time, the CTO of NVIDIA. Defendant does\n\nnot have knowledge or information sufficient to form a belief as to the truth of the allegations\n\nregarding the alleged communications between NVIDIA employees and Neurala made in 2007\n\nand on that basis denies them. Defendant admits that it became aware of the \u2019461 Patent since at\n\n\n\n\n 25\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 27 of\n 2647\n of 46\n\n\n\n\nleast the filing of this Complaint. Except as expressly admitted, Defendant denies the remaining\n\nallegations in Paragraph 161 of the Complaint.\n\n 162. Defendant admits that, in or around 2016, Defendant had discussions with Neurala,\n\nInc. and that at least Mr. Alvin Lin and/or Mr. Jeff Herbst from Defendant were involved.\n\nDefendant also admits that, in 2016, Defendant had discussions with at least one of the inventors\n\nregarding potential investments in Neurala, Inc. Defendant denies the remaining allegations in\n\nParagraph 162 of the Complaint.\n\n 163. Defendant admits that it hosted its GPU Technology Conference in May of 2017.\n\nTo the extent the allegations of Paragraph 161 purport to quote from or characterize the contents\n\nof websites, those websites speak for themselves. Defendant denies the remaining allegations in\n\nParagraph 163 of the Complaint.\n\n 164. Defendant denies the allegations in Paragraph 164 of the Complaint.\n\n 165. Defendant denies the allegations in Paragraph 165 of the Complaint.\n\n 166. Defendant denies the allegations in Paragraph 166 of the Complaint.\n\n 167. Defendant denies the allegations in Paragraph 167 of the Complaint.\n\n 168. Defendant denies the allegations in Paragraph 168 of the Complaint.\n\n 169. Defendant denies the allegations in Paragraph 169 of the Complaint.\n\n 170. Defendant denies the allegations in Paragraph 170 of the Complaint.\n\n 171. Defendant admits that it sells and has sold its products and provides certain\n\ntechnical support to its customers for those products. To the extent the allegations of Paragraph\n\n171 purport to quote from or characterize the contents of websites, those websites speak for\n\nthemselves. Defendant denies the remaining allegations in Paragraph 171 of the Complaint.\n\n 172. Defendant denies the allegations in Paragraph 172 of the Complaint.\n\n\n\n\n 26\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 28 of\n 2747\n of 46\n\n\n\n\n 173. Defendant denies the allegations in Paragraph 173 of the Complaint.\n\n 174. Defendant denies the allegations in Paragraph 174 of the Complaint.\n\n 175. Defendant denies the allegations in Paragraph 175 of the Complaint.\n\n 176. Defendant denies the allegations in Paragraph 176 of the Complaint.\n\n 177. Defendant denies the allegations in Paragraph 177 of the Complaint.\n\n PRAYER FOR RELIEF\n\n Defendant denies any factual assertions contained in Plaintiff\u2019s Prayer for Relief.\n\nDefendant further denies that Plaintiff is entitled to any relief whatsoever, including but not limited\n\nto the relief sought in Paragraphs A-G of the Complaint.\n\n DEMAND FOR JURY TRIAL\n\n A response is not required to Plaintiff\u2019s demand for a jury trial.\n\n DEFENSES\n\n Defendant repeats and re-alleges the allegations of the preceding Paragraphs as if fully set\n\nforth herein. Defendant asserts the following defenses to Plaintiff\u2019s Complaint, without admitting\n\nor acknowledging that Defendant bears the burden of proof as to any of them or that any must be\n\npleaded as defenses. Defendant specifically reserves all rights to allege additional defenses that\n\nbecome known through the course of discovery.\n\n FIRST DEFENSE\n (Non-Infringement)\n\n Defendant has not and does not infringe, either literally or under the doctrine of\n\nequivalents, any valid and enforceable claim of any Asserted Patent, whether directly, indirectly,\n\ncontributorily, by inducement, individually, jointly, willfully, or otherwise. Additionally, with\n\nrespect to Plaintiff\u2019s allegations of indirect, joint, and willful infringement, Defendant lacks the\n\nrequisite mens rea.\n\n\n\n 27\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 29 of\n 2847\n of 46\n\n\n\n\n SECOND DEFENSE\n (Invalidity & Ineligibility)\n\n The Asserted Claims are invalid under at least 35 U.S.C. \u00a7\u00a7 101, 102, 103, and/or 112.\n\nDefendant incorporates by reference its forthcoming invalidity contentions and all amendments\n\nthereto.\n\n THIRD DEFENSE\n (No Willfulness, Enhanced Damages, or Attorneys\u2019 Fees)\n\n Plaintiff is not entitled to enhanced damages under 35 U.S.C. \u00a7 284, at least because\n\nPlaintiff has failed to show, and cannot show, that any infringement has been willful and/or\n\nknowing. Plaintiff is not entitled to an award of attorney\u2019s fees under 35 U.S.C. \u00a7 285, at least\n\nbecause Plaintiff has failed to show, and cannot show, that this case is \u201cexceptional\u201d in Plaintiff\u2019s\n\nfavor as would be required by the statute.\n\n FOURTH DEFENSE\n (Statutory Limitation on Damages)\n\n Plaintiff\u2019s claims for relief are statutorily limited in whole or in part by 35 U.S.C. \u00a7\u00a7 286\n\nand/or 287. In addition, to the extent Plaintiff seeks damages for allegedly infringing acts\n\ncommitted more than six years prior to the filing of the Complaint in this action, it is barred from\n\nrecovery of such damages.\n\n Additionally, to the extent Plaintiff or any licensee of the Asserted Patent failed to properly\n\nmark any of their relevant products as required by 35 U.S.C. \u00a7 287 or otherwise failed to give\n\nproper notice that Defendant\u2019s actions allegedly infringed any Asserted Claim, Defendant is not\n\nliable to Plaintiff for the acts alleged to have been performed before Defendant received actual\n\nnotice of infringement.\n\n FIFTH DEFENSE\n (License, Exhaustion, Waiver, and Estoppel)\n\n Plaintiff\u2019s claims are barred, in whole or in part, by license, exhaustion, and/or the\n\n\n 28\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 30 of\n 2947\n of 46\n\n\n\n\ndoctrines of waiver and/or equitable estoppel.\n\n SIXTH DEFENSE\n (Inexcusable Delay)\n\n Plaintiff is barred from enforcing the Asserted Patents due to inexcusable delay in reviving\n\nthe \u2019867 patent after it was abandoned.\n\n SEVENTH DEFENSE\n (Intervening Rights)\n\n Plaintiff\u2019s claims are barred by the doctrine of absolute intervening rights and the doctrine\n\nof equitable intervening rights with respect to any Accused Product or technology that predates\n\nthe date of the revival of the \u2019867 patent and/or the date of the reissue of the \u2019461 and \u2019438 patents.\n\n35 U.S.C. \u00a7 252.\n\n EIGHTH DEFENSE\n (Improper Reissue)\n\n The claims of the \u2019438 and \u2019461 patents are invalid pursuant to 35 U.S.C. \u00a7 251 because\n\nthey enlarge the scope of the claims of the original patent and/or because they improperly recapture\n\nsubject matter that the patentee intentionally surrendered to obtain a valid patent.\n\n NINTH DEFENSE\n (28 U.S.C. \u00a7 1498)\n\n On information and belief, Plaintiff\u2019s claims against NVIDIA for patent infringement are\n\nbarred, in whole or in part, by 28 U.S.C. \u00a7 1498.\n\n TENTH DEFENSE\n (Ensnarement)\n\n Plaintiff is barred by the doctrine of ensnarement from contending that any Asserted Claim\n\ncovers any product, service, or method practiced, manufactured, used, sold, or offered for sale by\n\nDefendant in any manner that would ensnare the prior art.\n\n\n\n\n 29\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 31 of\n 3047\n of 46\n\n\n\n\n ELEVENTH DEFENSE\n (Territoriality)\n\n Plaintiff is not entitled to damages arising from any purported indirect infringement by\n\nDefendant that is premised on direct infringement by end-users occurring outside of the United\n\nStates under 35 U.S.C. \u00a7 271.\n\n TWELFTH DEFENSE\n (No Standing)\n\n Plaintiff\u2019s claims are barred because Plaintiff lacks standing to bring this suit. Specifically,\n\nPlaintiff cannot prove that it is the rightful owner of the Asserted Patents.\n\n THIRTEENTH DEFENSE\n (Failure to State a Claim)\n\n The Complaint fails to state a claim upon which relief may be granted.\n\n FOURTEENTH DEFENSE\n (Inconvenient Venue)\n\n For the convenience of parties and witnesses, venue for this action is not convenient\n\nin this district and would be more appropriate in another district. 28 U.S.C. \u00a7 1404.\n\n FIFTEENTH DEFENSE\n (Reservation of Defenses)\n\n Defendant reserves all affirmative defenses under Rule 8(c) of the Federal Rules of\n\nCivil Procedure, as well as any other defenses at law or in equity that may exist now or that may\n\nbe available in the future.\n\n SIXTEENTH DEFENSE\n (Unenforceability Due to Inequitable Conduct)\n\n 1. Each of the claims of the Asserted Patents is unenforceable due to inequitable\n\nconduct committed by prior assignee Neurala, one or more of the named inventors (Anatoli\n\nGorchetchnikov, Heather Marie Ames, Massimiliano Versace, and Fabrizio Santini), and/or\n\n\n\n\n 30\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 32 of\n 3147\n of 46\n\n\n\n\nprosecution counsel for prior assignee Neurala or current assignee NAI (including, but not limited\n\nto, Christopher Max Colice).\n\n 2. This case arises from a pattern of concealment and misrepresentation surrounding\n\na purported improvement to general-purpose computing on graphics processing units (\u201cGPGPU\u201d).\n\nLong before Neurala\u2019s initial patent application that led to the Asserted patents was filed, NVIDIA\n\nhad pioneered GPGPU computing, developing both the hardware and software foundations for\n\nexecuting general-purpose numerical computations on GPUs. NVIDIA\u2019s engineers\u2014through\n\ntechnologies such as BrookGPU and well-known books such as GPU Gems 2\u2014publicly disclosed\n\nthe very concepts later claimed by Neurala. These were not obscure academic papers; they were\n\nwell-known, widely cited works intended to teach the industry how to harness GPUs for scientific\n\ncomputing. Neurala and the named inventors were well aware of not only NVIDIA\u2019s role in\n\nGPGPU development, but of NVIDIA\u2019s specific teachings in GPU Gems 2 and other technologies.\n\n 3. Against this backdrop, the Asserted Patents claim a narrow and incremental\n\npurported improvement to GPGPU\u2014such as merely offloading certain setup and control functions\n\nfrom the host CPU to an \u201caccelerator controller.\u201d This supposed improvement did not create a\n\nnew GPGPU paradigm; it merely repeated well understood ideas from NVIDIA\u2019s prior work and\n\ncontributions to the field. Yet Neurala\u2019s inventors and attorneys withheld NVIDIA\u2019s key patents\n\nand publications\u2014including GPU Gems 2\u2014from the Patent Office while advancing their own\n\napplication.\n\n 4. There are two independent bases for an inequitable conduct finding, either of which,\n\nstanding alone, renders the Asserted Patents unenforceable. Together, they demonstrate a\n\ncoordinated pattern of misleading conduct intended to misdirect the Patent Office about the true\n\n\n\n\n 31\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 33 of\n 3247\n of 46\n\n\n\n\nstate of the art, the inventors\u2019 knowledge of it, and Neurala\u2019s desperate attempt to get patents on\n\ntechnology it did not invent.\n\n 5. Withholding of Material Prior Art. The claims of the Asserted Patents are\n\nunenforceable due to Neurala\u2019s and/or one or more of the named inventors\u2019 intentional withholding\n\nof material prior art references during prosecution of the Asserted Patents with an intent to deceive\n\nthe Patent Office.\n\n 6. False Declaration Regarding Abandonment. The claims of the Asserted Patents\n\nare also unenforceable due to Neurala\u2019s filing of a false declaration regarding abandonment of the\n\napplication that issued as the \u2019867 patent. Without that false declaration, none of the Asserted\n\nPatents would have issued.\n\n 7. Collectively, these acts form a coherent pattern of inequitable conduct\u2014a deliberate\n\neffort to obscure NVIDIA\u2019s pioneering role in GPGPU computing and to mislead the Patent Office\n\ninto granting patents on technology NVIDIA and others had already disclosed to the world.\n\nWithholding Material Prior Art\n\n 8. Neurala, each of the named inventors, and their counsel involved in the prosecution\n\nof the Asserted Patents had a duty of candor and good faith in dealing with the Patent Office, as\n\nrequired by 37 C.F.R. \u00a7 1.56. Their individual and collective failure to disclose known material\n\nprior art was done with specific intent to mislead or deceive the Patent Office into issuing each of\n\nthe Asserted Patents. As a result, all of the Asserted Patents are unenforceable due to inequitable\n\nconduct.\n\n\n\n\n 32\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 34 of\n 3347\n of 46\n\n\n\n\nKnowledge and Materiality of GPU Gems 2\n\n 9. Neurala, one or more of the named inventors, and/or Neurala\u2019s prosecution counsel\n\nintentionally withheld GPU Gems 2: Programming Techniques for High-Performance Graphics\n\nand General-Purpose Computation (\u201cGPU Gems 2\u201d) (March 2005) from the Patent Office.\n\n 10. NVIDIA published a series of books that provided practical guidance and\n\ntechniques for using GPUs in general-purpose applications, helping developers harness the parallel\n\nprocessing power of GPUs for a wide range of fields. One of those books was GPU Gems 2, which\n\nNVIDIA published on the Internet in March 2005 and made it available for download for free to\n\nanyone that wanted to download it. See Ex. 1 (April 1, 2025 Invalidity Contentions Ex. A11), Ex.\n\n2 (August 29, 2025 Supplemental Invalidity Contentions Supp. Ex. A11), Ex. 3 (April 1, 2025\n\nInvalidity Contentions App\u2019x B), Ex. 4 (April 1, 2025 Invalidity Contentions Ex. C11). At least\n\none of the named inventors\n\n\n\n . Despite extensive knowledge of GPU Gems 2 and its direct relevance for teaching\n\ntechniques for using GPUs in general-purpose applications, that inventor and Neurala withheld\n\nGPU Gems 2 from the Patent Office for all seven years that the \u2019867 patent was pending and every\n\nyear since.\n\n 11. not only was intimately familiar with GPU Gems 2 prior to the\n\nfiling of the provisional patent application from which the Asserted Patents claim priority but also\n\n\n\n\n 33\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 35 of\n 3447\n of 46\n\n\n\n\n 12. and one or more of the other named inventors met regularly to\n\ndiscuss the implementation of the project and the filing of the provisional patent application from\n\nwhich the Asserted Patents claim priority. See, e.g.,\n\nOn information and belief, the other named inventors and/or prosecution counsel were also aware\n\nof GPU Gems 2 due to the close nature of their working relationship with .\n\n 13. As NVIDIA detailed in its Invalidity Contentions served April 1, 2025, August 29,\n\n2025, and October 30, 2025, GPU Gems 2 is a prior art reference that is material to each of\n\nthe \u2019867, \u2019461, and \u2019438 patents. GPU Gems 2 anticipates the \u2019867 and \u2019438 patents and discloses\n\nkey elements of the \u2019461 patent claims. When combined with other unconsidered prior art,\n\nincluding NVIDIA\u2019s own patents, GPU Gems 2 renders obvious all of the Asserted Claims of the\n\nAsserted Patents. See Exs. 1, 2, 3, 4; see also Ex. 14 (April 1, 2025, Preliminary Invalidity\n\nContentions Cover Pleading), Ex. 15 (August 29, 2025 Supplemental Invalidity Contentions Cover\n\nPleading), Ex. 16 (October 30, 2025 Second Supplemental Invalidity Contentions Cover Pleading).\n\nThe Patent Office would not have allowed the \u2019867, \u2019461, or \u2019438 patents to issue but for the\n\nwithholding of GPU Gems 2. Therasense, Inc. v. Becton, Dickinson & Co., 649 F.3d 1276, 1290\u2013\n\n91 (Fed. Cir. 2011). For example, as NVIDIA details in its Invalidity Contentions with respect to\n\nclaim 16 of the \u2019867 patent, GPU Gems 2 teaches \u201can accelerator controller, operably coupled to\n\nthe accelerator memory and the central processing unit.\u201d See Ex. 1 at 15\u201344; Ex. 2; Ex. 17 (\u2019867\n\npatent file history) at 43. GPU Gems 2 teaches that the accelerator controller that \u201ctransfer[s] the\n\n\n\n\n 34\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 36 of\n 3547\n of 46\n\n\n\n\nat least the portion of the input data into the accelerator memory before the first computational\n\ncycle.\u201d See Ex. 1 at 27\u201344; Ex. 2; Ex. 17 at 43. GPU Gems 2 teaches that the accelerator controller\n\nthat \u201ctransfer[s] the first output data from the accelerator memory to the main memory during the\n\nsecond computational cycle\u201d and \u201cdirect[s] the second output data into the second partition during\n\nthe second computational cycle.\u201d See Ex. 1 at 54\u201369; Ex. 2; Ex. 17 at 43. GPU Gems 2 teaches\n\nthat the accelerator controller \u201cswap[s] the first pointer and the second pointer at the conclusion of\n\nthe second computational cycle such that the second output data becomes an input for a third\n\ncomputational cycle of the plurality of computational cycles.\u201d See Ex. 1 at 69\u201378; Ex. 2; Ex. 17\n\nat 43.\n\nKnowledge and Materiality of SANNDRA/KInNeSS\n\n 14. Mr. Gorchetchnikov and Mr. Massimiliano Versace\u2014named inventors of the\n\nAsserted Patents\u2014developed Synchronous Artificial Neuronal Networks Distributed Runtime\n\nAlgorithm (SANNDRA) and its implementation on KDE Integrated NeuroSimulation Software\n\n(KInNeSS) (\u201cSANNDRA/KInNeSS\u201d) (March 2005). SANNDRA version 1.1.x and KInNeSS\n\n0.3.3 (on which SANNDRA was implemented) were publicly available and in use by March 2005\n\nbased at least on the following information: KInNeSS: A new software environment for\n\nsimulations of neuronal activity; 9th International conference on Cognitive and Neural Systems\n\n(Boston, MA, 2004); https://web.archive.org/web/20051030032020/http://www.kinness.net/\n\n(KInNeSS documentation);\n\nhttps://web.archive.org/web/20080828055305fw /http://symphony.bu.edu/\n\nDocs/SANNDRA/html/index.html (SANNDRA API documentation); see also Ex. 5 (April 1, 2025\n\nInvalidity Contentions Ex. A7), Ex. 6 (April 1, 2025 Invalidity Contentions Ex. B7), Ex. 7 (April\n\n1, 2025 Invalidity Contentions Ex. C7).\n\n\n\n\n 35\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 37 of\n 3647\n of 46\n\n\n\n\n 15. Furthermore, the specification of the Asserted Patents acknowledges that\n\nSANNDRA \u201cwas developed to accelerate and optimize processing of numerical integration of\n\nlarge non-homogenous systems of differential equations.\u201d \u02bc867 patent at 9:25\u201235. And although\n\nthe Asserted Patents reference version 2.x.x of SANNDRA as \u201can example practical software\n\nimplementation of the method and architecture described above and pictorially represented in FIG.\n\n3,\u201d the applicant failed to identify previous, publicly available versions of SANNDRA or KInNeSS\n\nas relevant prior art to the Patent Office. Id.;\n\n\n\n Neurala, the named\n\ninventors, and their prosecution counsel further failed to fully disclose the relevance and\n\nmateriality of their own software to the Patent Office, despite being the ones in the best position\n\nto do so. NVIDIA expects further discovery, including complete production of the documents that\n\nNVIDIA requested from Neurala on July 30, 2025, to shed further light on Mr. Gorchetchnikov\u2019s\n\nand Mr. Versace\u2019s concealment of earlier versions of SANNDRA/KInNeSS.\n\n 16. SANNDRA 1.1.x and earlier versions, as implemented on KInNeSS, together with\n\nother undisclosed references (such as Nickolls and Kirk, among others) renders obvious all of the\n\nAsserted Claims of the Asserted Patents as shown by Exs. 5, 6, 7, and 16. The Patent Office would\n\nnot have allowed the \u2019867, \u2019461, or \u2019438 patents to issue but for the withholding of\n\nSANNDRA/KInNeSS. Therasense, 649 F.3d at 1290\u201391.\n\nKnowledge and Materiality of Cg\n\n 17. The C for Graphics (Cg) language (2003) is a high-level shading language created\n\nby NVIDIA in collaboration with Microsoft to program graphics shaders on GPUs. Cg was made\n\navailable as an open-source release and in public use by 2003 based at least on the following\n\n\n\n\n 36\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 38 of\n 3747\n of 46\n\n\n\n\ninformation: The Cg Tutorial: The Definitive Guide to Programmable Real-Time Graphics (2003);\n\nhttps://web.archive.org/web/20041205090713/http://developer.nvidia.com:80/object/cg_toolkit.h\n\ntml (\u201cCg Toolkit\u201d); see also Ex. 8 (April 1, 2025 Invalidity Contentions Ex. A4), Ex. 9 (April 1,\n\n2025 Invalidity Contentions Ex. B4), Ex. 10 (April 1, 2025 Invalidity Contentions Ex. C4).\n\n 18.\n\n\n\n 19. The Cg language, together with other references (such as Nickolls and Kirk, among\n\nothers) renders obvious all of the Asserted Claims of the Asserted Patents as shown by Exs. 8, 9,\n\n10, and 16. The Patent Office would not have allowed the \u2019867, \u2019461, or \u2019438 patents to issue but\n\nfor the withholding of Cg. Therasense, 649 F.3d at 1290\u201391.\n\nKnowledge and Materiality of BrookGPU\n\n 20. The BrookGPU programming language (2004) is an early system developed at\n\nStanford University to enable general-purpose computing on graphics processing units (GPGPU).\n\nBrookGPU was publicly available and in use by 2004 based at least on the following information:\n\nBuck et al., Brook for GPUs: Stream Computing on Graphics Hardware, ACM, 2004 (\u201cBrook for\n\nGPU 2004\u201d); https://web.archive.org/web/20041205061111/http://graphics.stanford.edu/projects/\n\nbrookgpu/start.html (BrookGPU documentation); see also Ex. 11 (April 1, 2025 Invalidity\n\nContentions Ex. A5), Ex. 12 (April 1, 2025 Invalidity Contentions Ex. B5), Ex. 13 (April 1, 2025\n\nInvalidity Contentions Ex. C5).\n\n 21.\n\n\n\n 22. The BrookGPU language, together with other references (such as Nickolls and Kirk,\n\namong others) renders obvious all of the Asserted Claims of the Asserted Patents, as shown by Exs.\n\n\n\n\n 37\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 39 of\n 3847\n of 46\n\n\n\n\n11, 12, 13, and 16. The Patent Office would not have allowed the \u2019867, \u2019461, or \u2019438 patents to\n\nissue but for the withholding of BrookGPU. Therasense, 649 F.3d at 1290\u201391.\n\nWithholding of Material References\n\n 23. Despite their awareness of numerous references relevant to the technology of the\n\nAsserted Patents, the named inventors did not provide any prior art to the Patent Office during\n\nprosecution of the \u02bc867 patent. Only four references are disclosed on the face of the \u2019867 patent\n\nas having been considered during prosecution, and all four were identified by the examiner in a\n\nNotice of References Cited. Although each of the four references cited by the examiner relates to\n\ngraphics rendering, none of the references provide the practical guidance and techniques for using\n\nGPUs in general-purpose applications that GPU Gems 2 does, or the relevant applied examples\n\nand implementations that system art, such as SANNDRA/KInNeSS, Cg, or BrookGPU provides.\n\nFor each of the two reissue patents, the applicant took the opposite approach and submitted\n\nhundreds of references, none of which was GPU Gems 2, SANNDRA/KInNeSS, Cg, or\n\nBrookGPU, and none of which provide the relevant applied examples and implementations that\n\nGPU Gems 2 does.\n\n 24. None of GPU Gems 2, SANNDRA/KInNeSS, Cg, or BrookGPU is cumulative of\n\nthe information already on record. Unlike the four graphics-rendering references cited by the\n\nexaminer, these materials disclose practical architectures, applied examples, and implementation-\n\nlevel guidance applicable to GPGPU\u2014the very subject matter of the Asserted Patents. But for\n\ntheir withholding, the Patent Office would not have allowed any of the \u2019867, \u2019461, or \u2019438 patents\n\nto issue. The deliberate withholding of these NVIDIA and other GPGPU-related references\n\ndeprived the examiner of the most relevant prior art and materially misled the Patent Office about\n\nthe true state of the art.\n\n\n\n\n 38\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 40 of\n 3947\n of 46\n\n\n\n\nIntent to Deceive\n\n 25. \u2014and by extension, Neurala\u2014knew of these material prior art\n\nreferences. On information and belief, the other named inventors and their counsel involved in\n\nprosecution were similarly aware of these references and knew of their materiality to the Asserted\n\nPatents. and others were aware of GPU Gems 2, SANNDRA/KInNeSS, Cg,\n\nor BrookGPU and made the conscious decision to withhold it from the Patent Office.\n\n 26. The inventors did not file their provisional application until September 25, 2006,\n\nover a year after first reviewed GPU Gems 2. And the inventors did not\n\ndisclose GPU Gems 2 to the Patent Office at any time during nearly seven years of prosecution of\n\nthe application that led to the \u2019867 patent.\n\n\n\n\n Each of these references was material and not\n\ncumulative of the bare record before the examiner during prosecution of the \u2019867 patent. It is\n\nsimply not credible that the named inventors did not think that any prior art was material to\n\nprosecution. These facts demonstrate an intent to deceive the Patent Office by not providing any\n\nprior art for its consideration. Thus, for the \u02bc867 patent, by withholding all known references, the\n\ninventors may have aimed to create a misleading impression of the uniqueness and inventiveness\n\nof their claims. For the two reissue patents, the applicant attempted to flood the Patent Office with\n\nreferences to distract from the key prior art that was omitted: GPU Gems 2, SANNDRA/KInNeSS,\n\nCg, and BrookGPU. These facts, and those yet to be ascertained through discovery demonstrate\n\nthat the most reasonable inference to draw is that the named inventors intended to deceive the\n\nPatent Office by withholding references during prosecution.\n\n\n\n\n 39\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 41 of\n 4047\n of 46\n\n\n\n\n 27. On information and belief, Neurala and the named inventors also intentionally\n\nchose not to disclose GPU Gems 2 to its attorneys responsible for prosecution of the patent\n\napplications at the Patent Office, knowing that such attorneys also owed a duty of candor to the\n\nPatent Office, and would disclose the reference to the Patent Office and the examiner if the\n\nattorneys were to become aware of it. In either case, Neurala and the named inventors violated\n\nthe duty of candor that each of them owed to the Patent Office.\n\n 28. A pattern of deceiving the Patent Office continues. For example, current assignee\n\nNeural AI recently paid the 11-year maintenance fee for the \u2019867 patent and did so with a\n\nrepresentation that it was entitled to small entity status, even though it knew it was no longer\n\nentitled to small entity status due to\n\n 29. These facts, when taken together with the evidence of intent presented for the other\n\nbasis of inequitable conduct, demonstrate a pattern of conduct that shows a continuing intent to\n\ndeceive the Patent Office.\n\nFiling a False Declaration Regarding Abandonment of an Application\n\n 30. In addition to failing to disclose material prior art references during the prosecution\n\nof the \u2019867 patent that, if cited, would have precluded the claims in that patent from issuing,\n\nNeurala and its prosecution counsel also affirmatively misled the Patent Office when it revived the\n\nabandoned application that issued as the \u2019867 patent. But for its misrepresentation, none of the\n\nAsserted Patents would have issued because the patent application from which all of those patents\n\nstem would have remained abandoned. This affirmative misrepresentation is part of Neurala\u2019s\n\ncontinued pattern of inequitable conduct in front of the Patent Office to obtain the Asserted Patents.\n\n 31. Specifically, Neurala and its prosecution counsel allowed the application that issued\n\nas the \u2019867 patent (U.S. Patent Appl. No. 11/860,254) (\u201cthe \u2019254 application\u201d) to become\n\n\n\n\n 40\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 42 of\n 4147\n of 46\n\n\n\n\nabandoned for more than two years before belatedly filing a false, generic declaration alleging that\n\nthe \u2019254 application had been unintentionally abandoned in an attempt to revive it. The claims of\n\neach of the Asserted Patents are therefore also unenforceable due to a false declaration regarding\n\nabandonment of the application that issued as the \u2019867 patent.\n\n 32. The application that issued as the \u2019867 patent (U.S. Patent Appl. No. 11/860,254)\n\n(\u201cthe \u2019254 application\u201d) was filed on September 24, 2007. The Patent Office issued a non-final\n\nOffice Action on September 16, 2010, with a three month non-statutory time period for reply. A\n\nresponse to the Office Action was due on December 16, 2010 without payment of extension fees,\n\nbut the applicant neither filed a response nor requested an extension of time under the provisions\n\nof 37 C.F.R. \u00a7 1.136(a), and the \u2019254 application became abandoned on December 17, 2010, the\n\nday after the expiration of the shortened non-statutory deadline established in the non-final Office\n\nAction.\n\n 33. On April 12, 2011, the Patent Office mailed a notice of abandonment to the\n\napplicant. It was not until July 31, 2013\u2014more than two years later\u2014that the applicant filed a\n\npetition to revive the \u2019254 application. The petition was signed by Christopher Max Colice of\n\nFoley & Lardner LLP and included the statement that \u201c[t]he entire delay in filing the required reply\n\nfrom the due date for the required reply until the filing of a grantable petition under 37 CFR 1.137(b)\n\nwas unintentional.\u201d Ex. 17 at 64\u201388. At the time, no power of attorney had been filed listing Mr.\n\nColice as Neurala\u2019s attorney of record. There is no indication in the statement what investigation\n\nMr. Colice undertook or how he determined that abandonment was \u201cunintentional.\u201d Furthermore,\n\nthe attorney advisor reviewing the petition noted that it was \u201cnot apparent whether the person\n\nsigning the statement of unintentional delay was in a position to have firsthand or direct knowledge\n\n\n\n\n 41\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 43 of\n 4247\n of 46\n\n\n\n\nof the facts and circumstances of the delay at issue,\u201d and that there was \u201cno indication that the\n\npetition [wa]s signed by a registered patent attorney or patent agent of record. Id. at 62.\n\n 34. Materiality. The material prong is met \u201c[w]hen the patentee has engaged in\n\naffirmative acts of egregious misconduct, such as the filing of an unmistakably false affidavit.\u201d\n\nTherasense, 649 F.3d at 1292; see also Rohm & Haas Co. v. Crystal Chem. Co., 722 F.3d 1556,\n\n1571 (Fed. Cir. 1983) (\u201cthere is no room to argue that submission of false affidavits is not\n\nmaterial\u201d); Intellect Wireless, Inc. v. HTC Corp., 732 F.3d 1339, 1342 (Fed. Cir. 2013); Apotex,\n\nInc. v. UCB, Inc., 763 F.3d 1354 (Fed. Cir. 2014). An affirmative act of egregious misconduct is\n\ninherently material. Therasense, 649 F.3d at 1292. The filing of a false revival petition under 37\n\nCFR \u00a7 1.137(a) is an affirmative act of egregious misconduct. In re Rembrandt Techs. LP Patent\n\nLitig., 899 F.3d 1254, 1272\u201374 (Fed. Cir. 2018). Because the \u02bc867 patent (which issued from the\n\n\u02bc254 application) was the first patent in the family, but for the false statement in the Petition for\n\nRevival, all Asserted Patents would not have issued and thus would no longer be in force. The\n\nfalse statement to the Patent Office is therefore material to patentability. See, e.g., 3D Med.\n\nImaging Sys. LLC v. Visage Imaging Inc., 228 F. Supp. 3d 1331, 1338\u201339 (N.D. Ga. 2017).\n\n 35. Intent. The intent of Mr. Colice and/or the named inventors to deceive the Patent\n\nOffice is evidenced at least by the length of time that elapsed between the dates of the Office\n\nAction (September 16, 2010), when the application became abandoned (December 18, 2010), the\n\nNotice of Abandonment (April 12, 2011), and the applicant\u2019s Petition for Revival (July 31, 2013).\n\nFor example, there is no explanation why it took almost three full years from when the Office\n\nAction was issued for the applicant to respond to the Office Action. Even after Neurala LLC was\n\nnotified of the abandonment, it took more than two years to file a Petition for Revival, accompanied\n\nby only a generic statement that the entire delay was unintentional. The most reasonable inference\n\n\n\n\n 42\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 44 of\n 4347\n of 46\n\n\n\n\nto draw is that there was an intent to allow the application to become abandoned, and that Mr.\n\nColice and/or the named inventors intended to deceive the Patent Office by submitting a false\n\ndeclaration stating that the abandonment of the \u2019254 application was unintentional.\n\n 36. The \u02bc254 application was the first application in the chain of applications for the\n\nAsserted Patents (it issued as the asserted \u02bc867 patent). If the \u02bc254 application had been deemed\n\nabandoned and no false declaration had been filed, no patents in the asserted patent family would\n\nhave issued. Therefore, all Asserted Patents should be rendered unenforceable due to the filing of\n\na false declaration in the prosecution of the \u02bc867 patent.\n\n 37. These facts, when taken together with the evidence of intent presented for the other\n\nbasis of inequitable conduct, demonstrate a pattern of conduct that shows a continuing intent to\n\ndeceive the Patent Office.\n\nInfectious Unenforceability\n\n 38. The \u02bc254 application\u2014from which the \u2019867 patent issued\u2014was the first application\n\nin the chain of applications for the Asserted Patents. Each of the \u2019461 and the \u2019438 patents is a\n\nchild of the \u2019867 patent, and the pattern of blatantly inequitable conduct that pervades the\n\nprosecution of this patent family renders the claims of each of the Asserted Patents unenforceable.\n\n 39. Here, but for the false declaration filed in support of the revival of the \u2019254\n\napplication, no patents in the asserted patent family would have ever issued. Lumenyte Intern.\n\nCorp. v. Cable Lite Corp., 96-1011, 1996 U.S. App. LEXIS 16400 (Fed. Cir. July 9, 1996) (a false\n\naffidavit filed to revive an abandoned patent results in the unenforceability of later-filed, related\n\npatents).\n\n 40. Additionally, but for the withholding of material prior art\u2014including GPU Gems\n\n2, Cg, SANNDRA/KInNeSS, and BrookGPU, the Patent Office would not have allowed any of\n\n\n\n\n 43\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 45 of\n 4447\n of 46\n\n\n\n\nthe Asserted Patents to issue. All of the Asserted Patents were procured through a pattern of\n\ninequitable conduct as discussed herein.\n\n 41. From withholding material prior art to falsely claiming unintentional abandonment\n\nto obtain a patent, Neurala, the named inventors, and prosecution counsel have exhibited a pattern\n\nof intentional deception of the Patent Office. The remedy for the repeated and egregious instances\n\nof inequitable conduct is to render each of the Asserted Patents unenforceable.\n\n PRAYER FOR RELIEF\n\n Wherefore, Defendant respectfully requests judgment in its favor with the following relief:\n\n a) The Complaint be dismissed with prejudice.\n\n b) Judgment that Defendant has not infringed and is not infringing, either directly or\n\n indirectly, any of the claims the \u2019867 Patent, the \u2019461 Patent, and the\u2019 438 Patent,\n\n in violation of 35 U.S.C. \u00a7 271.\n\n c) Judgment that the claims of the \u2019867 Patent, the \u2019461 Patent, and the\u2019 438 Patent\n\n are invalid.\n\n d) Judgment that the \u2019867 Patent, the \u2019461 Patent and the \u2019438 Patent, including all of\n\n their claims, are unenforceable due to inequitable conduct.\n\n e) Judgment and determination that this case is exceptional under 35 U.S.C. \u00a7 285 and\n\n that Defendant is entitled to its attorneys\u2019 fees, costs, and expenses in defending\n\n this action.\n\n f) Such other relief, including other monetary and equitable relief, as this Court deems\n\n just and proper.\n\n DEMAND FOR JURY TRIAL\n\n Defendant demands a jury trial on all issues so triable.\n\n\n\n\n 44\n\f Case\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 46 of\n 4547\n of 46\n\n\n\n\nDated: November 18, 2025\n\n /s/ L. Kieran Kieckhefer\n L. Kieran Kieckhefer (pro hac vice)\n Jaysen S. Chung (pro hac vice)\n GIBSON, DUNN & CRUTCHER LLP\n One Embarcadero Center, Suite 2600\n San Francisco, CA 94111\n (415) 393-8200\n kkieckhefer@gibsondunn.com\n jschung@gibsondunn.com\n\n Brian Rosenthal\n Ahmed ElDessouki (pro hac vice)\n GIBSON, DUNN & CRUTCHER LLP\n 200 Park Ave.\n New York, NY 10166\n (212) 351-4000\n brosenthal@gibsondunn.com\n aeldessouki@gibsondunn.com\n\n Lillian J. Mao (pro hac vice)\n GIBSON DUNN & CRUTCHER LLP\n 1881 Page Mill Road\n Palto Alto, CA 94301-1211\n (650) 849-5307\n lmao@gibsondunn.com\n\n Barry K. Shelton (Texas State Bar No. 24055029)\n SHELTON COBURN LLP\n 311 RR 620 S, Suite 205\n Austin, TX 78734\n (512) 263 2165\n bshelton@sheltoncoburn.com\n\n Counsel for Defendant NVIDIA Corporation\n\n\n\n\n 45\n\fCase\n Case\n 7:24-cv-00221-ADA-DTG\n 7:26-mc-00324-DC Document\n Document\n 1-9130Filed\n Filed\n 08/18/26\n 11/25/25Page\n Page\n 47 of\n 4647\n of 46\n\n\n\n\n CERTIFICATE OF SERVICE\n\n I hereby certify that all counsel of record are being served with a copy of the foregoing\n\n documents via electronic mail on November 18, 2025.\n\n /s/ L. Kieran Kieckhefer\n L. Kieran Kieckhefer\n\n\n\n\n 46\n\f","ocr_status":2,"date_upload":"2026-08-20T10:55:18.062985-07:00","document_number":"1","attachment_number":9,"pacer_doc_id":"181037219904","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 8","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514523/","id":490514523,"tags":[],"absolute_url":"/docket/74667129/1/10/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.090274-07:00","date_modified":"2026-08-23T08:26:14.526264-07:00","sha1":"9d3201055f33f454daf58c2baa72d34fe39343f1","page_count":34,"file_size":298353,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.10.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.10.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 1 of 34\n\n\n\n\n EXHIBIT\n\n 9\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 2 of 34\n\n\n\n\n IN THE UNITED STATES DISTRICT COURT\n WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\n\nNEURAL AI, LLC,\n\n Plaintiff, Civil Action No. 7:24-cv-00221-ADA-DTG\n\n v.\n\nNVIDIA CORPORATION,\n\n Defendant.\n\n\nNONPARTY GOOGLE LLC\u2019S OBJECTIONS AND RESPONSES TO NEURAL AI, LLC\u2019S\n SUBPOENA TO PRODUCE DOCUMENTS, INFORMATION, OR OBJECTS\n\n Pursuant to Federal Rules of Civil Procedure 26 and 45, non-party Google LLC (\u201cGoogle\u201d)\n\nhereby submits its Objections and Responses to the Subpoena to Produce Documents, Information,\n\nor Objects (the \u201cSubpoena\u201d) served by Plaintiff Neural AI, LLC (\u201cNAI\u201d) on or about June 24, 2026,\n\nin connection with the above-captioned action. Google makes these Objections and Responses\n\nbased on its current knowledge, information, and belief following a reasonable inquiry. Google\n\nreserves the right to supplement or amend these Objections and Responses as additional information\n\nbecomes available.\n\n PRELIMINARY STATEMENT\n\n Google responds to the Subpoena subject to the accompanying objections. Google is a non-\n\nparty to this matter, is not involved in the underlying dispute, and has not otherwise engaged in\n\ndiscovery with the parties. All of the responses contained herein, therefore, are based only upon\n\nsuch limited information and documents as are presently available to and specifically known to\n\nGoogle. The following responses are given without prejudice to Google\u2019s right to produce any\n\n\n\n -1-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 3 of 34\n\n\n\n\nsubsequently discovered information or facts that Google may discover. Google, accordingly,\n\nreserves the right to change any and all responses herein if additional facts are ascertained, analyses\n\nare made, research is completed, or contentions are made.\n\n GENERAL OBJECTIONS\n\n The following General Objections apply to and are incorporated by reference into each of\n\nthe specific responses and objections set forth below, as if fully set forth therein. Google\u2019s assertion\n\nof any specific objection in response to a particular Request does not waive any General Objection.\n\nGoogle reserves the right to supplement, amend, or correct these responses and objections as\n\nadditional information becomes available.\n\n 1. Obligations in Excess of Federal Rules. Google objects to the Subpoena\u2019s\n\ndefinitions and instructions to the extent they purport to impose obligations on Google in excess of\n\nany applicable federal or state codes of civil procedure, rules of evidence, or any other applicable\n\nlaw.\n\n 2. Improper place of compliance. Google objects to this Subpoena to the extent the\n\nplace of compliance\u2014Planet Depos, Downtown Austin, 100 Congress Ave., Ste. 2000, Austin, TX\n\n78701\u2014does not satisfy Rule 45(c)(2)(A) of the Federal Rules of Civil Procedure. Rule 45 permits\n\nproduction \u201cat a place within 100 miles of where the person resides, is employed, or regularly\n\ntransacts business in person.\u201d The relevant inquiry under Rule 45 is not simply whether Google has\n\nsome business presence anywhere within 100 miles of the specified location, but whether the\n\ncustodians of records whose files would be responsive to the Subpoena reside, are employed, or\n\nregularly transact business in person within 100 miles of the designated compliance location.\n\nGoogle\u2019s principal place of business is in Mountain View, California, and the employees most\n\nknowledgeable about and in possession of documents responsive to the Requests would be located\n\n\n -2-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 4 of 34\n\n\n\n\nin or near Google's headquarters, not in Austin, Texas. Notwithstanding this objection, and without\n\nwaiving it, Google responds as set forth below to preserve a cooperative record.\n\n 3. Undue Burden on a Non-Party. Google objects to the Subpoena on the grounds\n\nthat it seeks to impose an undue burden on Google, which is not a party to the underlying action.\n\nGoogle further objects to the Subpoena to the extent it seeks documents or information that is in the\n\npossession, custody, or control of a party to the underlying action, such as NVIDIA Corporation, or\n\nequally available from another source (including public sources) that is more convenient, less\n\nburdensome, or less expensive than requiring Google to produce such documents or information.\n\nAs a disinterested non-party, Google should not be subjected to the burden of searching for and\n\nproducing such documents or information unless and until all reasonable means of obtaining that\n\ninformation directly from such other sources have been exhausted.\n\n 4. Unreasonable Search. Google objects to the Subpoena to the extent it purports to\n\nrequire Google to perform anything more than a reasonable and diligent search for documents\n\n(including electronic documents) from reasonably accessible sources (including electronic sources)\n\n 5. Overbreadth and Lack of Proportionality. Google objects to the Subpoena to the\n\nextent it seeks documents or information that are not proportionate to the needs of the case or not\n\nrelevant to any party\u2019s claims or defenses. Moreover, because neither a copy of the underlying\n\ncomplaint nor a description of the underlying claims at issue accompanied the Subpoena, Google is\n\nunable to discern whether the documents or information sought by the Subpoena are discoverable,\n\nand what its obligations are, if any, to respond to the Subpoena. Google objects to each Request to\n\nthe extent it is overly broad, seeks information that is not relevant to the claims or defenses in the\n\nunderlying action, and is not proportional to the needs of the case as required by Fed. R. Civ. P.\n\n26(b)(1). Google also objects to the Requests as overly broad and unduly burdensome to the extent\n\n\n -3-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 5 of 34\n\n\n\n\nthey seek \u201cAll Documents\u201d or \u201cAll Communications\u201d with respect to a subject because such\n\nomnibus requests seek discovery that is not relevant to a party\u2019s claim or defense and are not\n\nproportional to the needs of the case.\n\n 6. Vague, Overbreadth, and Lack of Proportionality. Google objects to the\n\ndefinition of \u201cNVIDIA GPUs,\u201d which alone spans three full pages and encompasses hundreds of\n\nGPU architectures and hundreds of individual GPU products. Requests defined in terms of this\n\nexpansive definition\u2014and further qualified by omnibus definitions equating \u201cor\u201d with \u201cand\u201d and\n\n\u201cany\u201d with \u201call\u201d\u2014are facially overbroad. Google objects to the definition of \u201cNVIDIA GPU\u201d as\n\nvague, overbroad, unduly burdensome and disproportionate to the needs of the case to the extent it\n\nincludes over 240 different devices in addition to \u201cany and all variations of the aforementioned\n\nproducts (including at least products having different options for number of GPUs.\u201d Google also\n\nobjects to this definition as unduly burdensome and disproportionate to the needs of the case to the\n\nextent it purports to require Google to determine what specific products fall within plaintiff\u2019s\n\ndefinition. Google will not attempt to interpret this term. Google objects to this definition to the\n\nextent it requires an expert or legal opinion. Google also objects to Instruction No. 23, which uses\n\nthe terms \u201cNVIDIA GPU-Acceleration Hardware\u201d and \u201cNVIDIA GPU-Acceleration Software,\u201d but\n\nnowhere are those terms defined, and hence they are vague, overbroad, and unduly burdensome.\n\nGoogle will not attempt to interpret these terms.\n\n Google also objects to the definition of \u201cSource Code\u201d as vague, overbroad, unduly\n\nburdensome, and disproportionate to the needs of the case. The definition purports to encompass\n\nnot only human-readable programming instructions but also \u201call comments, annotations,\n\ndeclarations, functions, classes, and other components used to define the behavior of a software\n\nprogram,\u201d \u201call associated files necessary to understand, compile, and execute the code, such as\n\n\n -4-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 6 of 34\n\n\n\n\nscripts, header files, makefiles, configuration files, and documentation,\u201d as well as \u201call versions and\n\nrevisions relevant to the time periods and subject matter described in each interrogatory.\u201d As\n\ndefined, \"Source Code\" effectively sweeps in Google\u2019s entire software development history for any\n\nsystem touching NVIDIA GPUs. Google also objects that \u201cnecessary to understand\u201d is vague and\n\nambiguous and subjective. Google further objects to this definition to the extent it seeks Source\n\nCode that constitutes Google's most sensitive trade secret and proprietary information. Compelling\n\na non-party to produce source code is an extraordinary measure that requires, at minimum, a\n\nshowing of substantial need that NAI has not made. Such production would also require entry of a\n\nprotective order providing source code-level protections\u2014which has not been established. Google\n\nwill not produce Source Code, as defined, absent such a showing and such protections. To the extent\n\nany specific Request incorporates this definition, Google objects to that Request on these same\n\ngrounds.\n\n Google also objects to the definitions of \u201cconcerning,\u201d \u201crelated to,\u201d and \u201cregarding\u201d\n\nencompass over a dozen different verbs in a deliberately all-inclusive formulation that renders\n\nvirtually any document potentially responsive to any Request. Google will interpret each Request\n\nreasonably and in good faith. Google also objects to the definition of \u201cYou\u201d or \u201cYour\u201d as overbroad,\n\nunduly burdensome, and disproportionate to the needs of the case. As defined, the terms purport to\n\nencompass not only Google LLC itself but also its predecessors, successors, parents, subsidiaries,\n\ndivisions, affiliates, and all past or present directors, officers, partners, managers, employees,\n\ncontractors, agents, representatives, accountants, consultants, in-house and outside counsel, and any\n\nother person or entity acting or purporting to act on its behalf or subject to its control. The definition\n\nfurther expressly extends to any Google parent, subsidiary, affiliate, or other related entity that has\n\n\u201cused, licensed, deployed, evaluated, or integrated NVIDIA GPUs or software.\u201d As defined, \u201cYou\u201d\n\n\n -5-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 7 of 34\n\n\n\n\nand \u201cYour\u201d would require Google to conduct an unduly burdensome undertaking to determine who\n\nmay fit into this definition, and then search for and produce documents from those source, including\n\nthose not within Google LLC's own possession, custody, or control, and to undertake an\n\ninvestigation spanning entities and individuals that are legally distinct from Google LLC and over\n\nwhose documents and information Google LLC may have no authority to collect or produce.\n\nGoogle further objects to this definition to the extent it purports to impose discovery obligations on\n\nGoogle\u2019s in-house and outside counsel, whose documents and communications are protected by the\n\nattorney-client privilege and work product doctrine. Google further objects to the catch-all phrase\n\n\u201cany other person or entity acting or purporting to act on its behalf or subject to its control\u201d as vague,\n\nundefined, and potentially limitless in scope. Google will interpret \u201cYou\u201d and \u201cYour\u201d to refer solely\n\nto Google LLC, and will respond to the Requests based on a reasonable search of Google LLC\u2019s\n\nown files, consistent with its obligations under Federal Rule of Civil Procedure 45.\n\n 7. Confidential and Proprietary Information. Google objects to the Subpoena to the\n\nextent it seeks confidential financial, proprietary or trade secret information belonging to Google or\n\na third party, or any other information subject to a confidentiality agreement, protective order or\n\nlegal duty of non-disclosure (\u201cConfidential Information\u201d). Google will only produce information it\n\ndeems confidential pursuant to a confidentiality agreement or protective order that it believes is\n\nsuitable for the protection of its Confidential Information. Even if an adequate protective order has\n\nbeen entered in the underlying action by the presiding court, Google will only provide Confidential\n\nInformation to the extent Google can do so consistent with its legal, contractual and other\n\nconfidentiality obligations. Google reserves the right to redact Confidential Information belonging\n\nto Google or third parties, as well as information concerning irrelevant matters.\n\n 8. Electronically Stored Information Burden. Google objects to the extent the\n\n\n -6-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 8 of 34\n\n\n\n\nRequests seek source code or the equivalent of a full source code review. Producing source code or\n\nconducting the equivalent investigation is extraordinarily burdensome even for a party, let alone a\n\nnon-party. The Court\u2019s own Standing Order Governing Proceedings (OGP) in Patent Cases states\n\nthat \u201cthe Court will not require general search and production of email or other electronically stored\n\ninformation (ESI) related to email (such as metadata), absent a showing of good cause.\u201d The same\n\nproportionality principles apply here. See Standing Order Governing Proceedings (OGP) 4.4-Patent\n\nCases, p. 3.\n\n 9. Email and Communications. Google specifically objects to any Request that\n\nrequires the collection, review, and production of emails or other internal communications as\n\nfacially overbroad and unduly burdensome on a non-party.\n\n 10. Privilege. Google objects to the Subpoena to the extent it seeks information\n\nprotected by any privilege, including the attorney-client privilege, work product immunity doctrine,\n\ncommon interest privilege, or any other applicable privilege, immunity, or restriction on discovery.\n\nAny disclosure of privileged information by Google in response to the Subpoena shall not be deemed\n\na waiver of any such privilege, and Google expressly requests that any party that receives any such\n\nprivileged information produced by Google immediately return and do not make use of any\n\nproduced privileged information.\n\n 11. Relevance to Underlying Claims. Google objects to each Request to the extent it\n\nlacks a demonstrated nexus to the patents-in-suit or to any specific claim of direct, indirect, or\n\ninduced infringement by NVIDIA. Google\u2019s internal use of any products has no necessary bearing\n\non whether NVIDIA\u2019s products infringe NAI\u2019s patents. Mere customer status does not render a\n\nnon-party\u2019s internal documents, communications, or financial information relevant to a patent\n\ninfringement suit against the manufacturer.\n\n\n -7-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 9 of 34\n\n\n\n\n 12. Temporal and Geographic Scope. Google objects to the temporal scope of\n\nSeptember 13, 2018 to the present to the extent it encompasses time periods or activities not relevant\n\nto the specific claims and accused products at issue. Google also objects to the Subpoena\u2019s\n\npurported reach over non-U.S. activity \u201cthat directly supports or enables U.S. operations\u201d (see, e.g.,\n\nInstruction No. 23) as vague, overbroad, and potentially reaching activity entirely outside the\n\nCourt\u2019s jurisdiction.\n\n 13. Date and Time of Compliance. Google objects to the date and time set for\n\ncompliance as unreasonable, inconvenient, and unduly burdensome. The date and time were selected\n\nunilaterally by NAI without consulting Google or its counsel regarding availability, and without\n\nmaking any effort to identify a mutually agreeable time and place for compliance. Google further\n\nobjects that the time provided for compliance is insufficient to permit Google to conduct a\n\nreasonable and diligent investigation across its organization, identify potentially responsive\n\ndocuments and information, and review those materials for privilege and confidentiality. This is\n\nparticularly true given the breadth and technical complexity of the Requests, which, as set forth in\n\nGoogle's specific objections below, implicate highly sensitive and technically complex aspects of\n\nGoogle's computing infrastructure. To the extent Google produces documents or a witness in\n\nresponse to the Subpoenas, it will do so at a mutually agreeable date, time, and place to be negotiated\n\nwith NAI's counsel following the parties\u2019 meet and confer.\n\n 14. Google reserves the right to assert additional objections, or to supplement its\n\nobjections and responses as appropriate, particularly if any additional information regarding the\n\nSubpoena or the underlying claims at issue is provided.\n\n\n\n SPECIFIC OBJECTIONS AND RESPONSES TO REQUESTS FOR PRODUCTION\n\n\n -8-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 10 of 34\n\n\n\n\nREQUEST NO. 1:\n\n Documents sufficient to identify all software, frameworks, libraries, APIs, scripts, Source\n\nCode, configuration files, and custom code You use to perform computations on NVIDIA GPUs.\n\nRESPONSE TO REQUEST NO. 1:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a nonparty\u2014as it seeks an exhaustive catalog of every piece of software,\n\nframework, library, API, script, source code, configuration file, and custom code that Google\n\npurportedly uses with NVIDIA GPUs; (2) it seeks information that is not within Google\u2019s\n\npossession, custody or control; (3) it seeks electronically stored information that is not reasonably\n\naccessible by Google without undue burden and/or cost; (4) it calls for information that Google is\n\nnot capable of producing (or not reasonably able to produce); (5) lacks relevance, including but not\n\nlimited to because this Request lacks a demonstrated nexus to the specific patents-in-suit and the\n\nspecific accused NVIDIA products and software combinations; (6) it seeks information that is highly\n\nconfidential, proprietary, that contains trade secrets, that contains personally identifiable\n\ninformation, and/or is subject to a confidentiality agreement or protective order; (7) it seeks\n\ninformation that is not proportionate to the needs of the case and not relevant to any party's claims\n\nor defenses; (8) it uses overbroad, vague and ambiguous terms and phrases in the request, including,\n\nbut not limited to \u201cYou\u201d and \u201cSource Code\u201d (see Objection 6 above), \u201cframeworks,\u201d \u201clibraries,\u201d\n\n\u201cAPIs,\u201d \u201cscripts,\u201d \u201cconfiguration files,\u201d \u201ccustom code,\u201d without providing additional identifying or\n\nclarifying information to explain exactly what is sought; (9) it is improper because it is an\n\ninterrogatory disguised as a document request; (10) given the definition of NVIDIA GPUs, this\n\n\n -9-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 11 of 34\n\n\n\n\nrequest amounts to over 240 requests and thus is overbroad, unduly burdensome, and not\n\nproportional. Google further objects to this request as unduly burdensome to the extent it seeks\n\ndocuments that are over seven years old. Such documents, to the extent they exist, may reside in\n\ndifficult-to-access sources. Google is not able to retrieve information from many of these sources,\n\nor even confirm with certainty whether any responsive information in fact exists in the sources,\n\nwithout incurring substantial undue burden or cost. Google further objects to this request to the\n\nextent that it seeks information protected by the attorney-client privilege, attorney work product\n\ndoctrine, or any other applicable protection.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\nREQUEST NO. 2:\n\n Documents sufficient to show whether You use NVIDIA\u2019s Aerial, Clara Parabricks,\n\ncuBLAS, cuDNN, cuFFT, cuQuantum, cuSOLVER, cuSPARSE, Drive, DriveWorks, Holoscan,\n\nIsaac, Isaac Lab, Maxine, Memory Map, Merlin, Metropolis, Modulus, Monai, Morpheus, NeMo,\n\nPyTorch, RAPIDS, Riva, Runtime Driver, TensorFlow, TensorRT, Triton, VSS (Deepstream), or\n\nany other NVIDIA software as part of computations You perform using NVIDIA GPUs.\n\nRESPONSE TO REQUEST NO. 2:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a nonparty\u2014as it seeks information about over twenty named NVIDIA\n\nsoftware products, plus a catch-all for \u201cany other NVIDIA software,\u201d with no limitation as to the\n\nsoftware operation that is relevant; (2) it seeks information that is not within Google\u2019s possession,\n\n\n -10-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 12 of 34\n\n\n\n\ncustody or control; (3) it seeks electronically stored information that is not reasonably accessible by\n\nGoogle without undue burden and/or cost; (4) it calls for information that Google is not capable of\n\nproducing (or not reasonably able to produce); (5) lacks relevance, including but not limited to\n\nbecause this Request lacks a demonstrated nexus to the specific patents-in-suit and the specific\n\naccused NVIDIA products and software; (6) it seeks information that is highly confidential,\n\nproprietary, that contains trade secrets, and/or is subject to a confidentiality agreement or protective\n\norder; (7) it seeks information that is not proportionate to the needs of the case and not relevant to\n\nany party's claims or defenses; (8) it uses overbroad, vague and ambiguous terms and phrases in the\n\nrequest, including, but not limited to \u201cYou\u201d (see Objection 6 above), \u201cother NVIDIA software,\u201d\n\n\u201ccomputations You perform using NVIDIA GPUs,\u201d without providing additional identifying or\n\nclarifying information to explain exactly what is sought; (9) it is improper because it is an\n\ninterrogatory disguised as a document request; (10) given the definition of NVIDIA GPUs, this\n\nrequest amounts to over 240 requests and thus is overbroad, unduly burdensome, and not\n\nproportional. Google further objects to this request to the extent that it seeks information protected\n\nby the attorney-client privilege, attorney work product doctrine, or any other applicable protection.\n\nGoogle further objects to this request as unduly burdensome to the extent it seeks documents that\n\nare over seven years old. Such documents, to the extent they exist, may reside in difficult-to-access\n\nsources. Google is not able to retrieve information from many of these sources, or even confirm\n\nwith certainty whether any responsive information in fact exists in the sources, without incurring\n\nsubstantial undue burden or cost.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\nREQUEST NO. 3:\n\n\n -11-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 13 of 34\n\n\n\n\n Documents sufficient to show whether You use sample Source Code provided by NVIDIA\n\nas part of computations You perform using NVIDIA GPUs.\n\nRESPONSE TO REQUEST NO. 3:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope, especially for a nonparty; (2) it is vague and ambiguous as to the phrases \u201cYou\u201d and\n\n\u201cSource Code\u201d (see Objection 6 above), \u201csample Source Code provided by NVIDIA\u201d; (3) it seeks\n\ninformation that is not within Google\u2019s possession, custody or control; (4) it seeks electronically\n\nstored information that is not reasonably accessible by Google without undue burden and/or cost;\n\n(5) it calls for information that Google is not capable of producing (or not reasonably able to\n\nproduce); (6) it seeks information already in the possession of a party to the litigation; (7) it seeks\n\ninformation that is highly confidential, proprietary, that contains trade secrets, and/or is subject to a\n\nconfidentiality agreement or protective order; (8) it seeks information that is not proportionate to\n\nthe needs of the case and not relevant to any party\u2019s claims or defenses; (9) lacks relevance,\n\nincluding but not limited to because this Request lacks a demonstrated nexus to the specific patents-\n\nin-suit and the specific accused NVIDIA products and software; (10) it uses overbroad, vague and\n\nambiguous terms and phrases in the request, including, but not limited to \u201ccomputations You\n\nperform using NVIDIA GPUs\u201d without providing additional identifying or clarifying information\n\nto explain exactly what is sought; (11) it is improper because it is an interrogatory disguised as a\n\ndocument request; (12) given the definition of NVIDIA GPUs, this request amounts to over 240\n\nrequests and thus is overbroad, unduly burdensome, and not proportional. Google further objects\n\nto this request to the extent that it seeks information protected by the attorney-client privilege,\n\n\n -12-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 14 of 34\n\n\n\n\nattorney work product doctrine, or any other applicable protection. Google further objects to this\n\nrequest as unduly burdensome to the extent it seeks documents that are over seven years old. Such\n\ndocuments, to the extent they exist, may reside in difficult-to-access sources. Google is not able to\n\nretrieve information from many of these sources, or even confirm with certainty whether any\n\nresponsive information in fact exists in the sources, without incurring substantial undue burden or\n\ncost.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\nREQUEST NO. 4:\n\n Documents sufficient to show whether and how any software You use to perform\n\ncomputations on NVIDIA GPUs calls, invokes, interfaces with, wraps, depends on, sits on top of,\n\nmodifies, extends, or implements functionality provided by CUDA, cuDNN, TensorRT, CUDA\n\nlibraries, CUDA drivers, CUDA runtime, CUDA applications or frameworks or any other NVIDIA\n\nsoftware.\n\nRESPONSE TO REQUEST NO. 4:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a nonparty\u2014with its string of alternative verbs (calls, invokes, interfaces\n\nwith, wraps, depends on, sits on top of, modifies, extends, implements) and catchall request for \u201cany\n\nother NVIDIA software effectively asking Google to produce a comprehensive technical map of\n\nhow all of its software that runs on NVIDIA hardware interacts with NVIDIA\u2019s software stack; (2)\n\nit is vague and ambiguous as to the phrases \u201cYou\u201d (see Objection 6 above), \u201ccalls, invokes,\n\n\n -13-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 15 of 34\n\n\n\n\ninterfaces with, wraps, depends on, sits on top of, modifies, extends, or implements functionality\n\nprovided by\u201d; (3) it seeks information that is not within Google\u2019s possession, custody or control; (4)\n\nit seeks electronically stored information that is not reasonably accessible by Google without undue\n\nburden and/or cost; (5) it calls for information that Google is not capable of producing (or not\n\nreasonably able to produce); (6) it seeks information already in the possession of a party to the\n\nlitigation; (7) it seeks information that is highly confidential, proprietary, that contains trade secrets,\n\nthat contains personally identifiable information, and/or is subject to a confidentiality agreement or\n\nprotective order; (8) it seeks information that is not proportionate to the needs of the case and not\n\nrelevant to any party's claims or defenses; (9) it lacks relevance, including but not limited to because\n\nthis Request lacks a demonstrated nexus to the specific patents-in-suit and the specific accused\n\nNVIDIA products and software; (10) it uses overbroad, vague and ambiguous terms and phrases in\n\nthe request, including, but not limited to \u201chow any software You use to perform computations on\n\nNVIDIA GPUs,\u201d \u201ccalls,\u201d \u201cinvokes,\u201d \u201cinterfaces with,\u201d \u201cwraps,\u201d \u201cdepends on,\u201d \u201csits on top of,\u201d\n\n\u201cmodifies,\u201d \u201cextends,\u201d or \u201cimplements functionality provided by CUDA, cuDNN, TensorRT,\n\nCUDA libraries, CUDA drivers, CUDA runtime, CUDA applications,\u201d \u201cframeworks,\u201d \u201cor any other\n\nNVIDIA software,\u201d without providing additional identifying or clarifying information to explain\n\nexactly what is sought; (11) it is improper because it is an interrogatory disguised as a document\n\nrequest; (12) given the definition of NVIDIA GPUs, this request amounts to over 240 requests and\n\nthus is overbroad, unduly burdensome, and not proportional. Google further objects to this request\n\nto the extent that it seeks information protected by the attorney-client privilege, attorney work\n\nproduct doctrine, or any other applicable protection. Google further objects to this request as unduly\n\nburdensome to the extent it seeks documents that are over seven years old. Such documents, to the\n\nextent they exist, may reside in difficult-to-access sources. Google is not able to retrieve information\n\n\n -14-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 16 of 34\n\n\n\n\nfrom many of these sources, or even confirm with certainty whether any responsive information in\n\nfact exists in the sources, without incurring substantial undue burden or cost.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\nREQUEST NO. 5:\n\n Documents sufficient to show the architecture, design, data flow, control flow, and execution\n\nflow of any system in which You use NVIDIA GPUs to perform computations, including diagrams,\n\ntechnical specifications, design documents, Powerpoints, slide decks, internal and external\n\npresentations, Source Code, configuration files, build files, deployment files, runtime logs, and\n\nprofiler traces.\n\nRESPONSE TO REQUEST NO. 5:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a nonparty\u2014with its request for an overbroad category of technical\n\ninformation for \u201carchitecture, design, data flow, control flow, and execution flow of any system in\n\nwhich You use NVIDIA GPUs to perform computations\u201d and documents encompassing \u201cdiagrams,\n\ntechnical specifications, design documents, Powerpoints, slide decks, internal and external\n\npresentations, Source Code, configuration files, build files, deployment files, runtime logs, and\n\nprofiler traces\u201d; (2) it is vague and ambiguous as to the phrases \u201cYou\u201d (see Objection 6 above),\n\n\u201cperform computations\u201d; (3) it seeks information that is not within Google\u2019s possession, custody or\n\ncontrol; (4) it seeks electronically stored information that is not reasonably accessible by Google\n\nwithout undue burden and/or cost; (5) it calls for information that Google is not capable of producing\n\n\n -15-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 17 of 34\n\n\n\n\n(or not reasonably able to produce); (6) it seeks information already in the possession of a party to\n\nthe litigation; (7) it seeks information that is highly confidential, proprietary, that contains trade\n\nsecrets, and/or is subject to a confidentiality agreement or protective order; (8) it seeks information\n\nthat is not proportionate to the needs of the case and not relevant to any party\u2019s claims or defenses,\n\nas it seeks information about Google\u2019s systems that use NVIDIA GPUs, not limited to the accused\n\nfunctionality of the NVIDIA GPUs relevant to the underlying action and for which NAI cannot\n\nobtain from NVIDIA itself; (9) it lacks relevance, including but not limited to because this Request\n\nlacks a demonstrated nexus to the specific patents-in-suit and the specific accused NVIDIA products\n\nand software; (10) it uses overbroad, vague and ambiguous terms and phrases in the request,\n\nincluding, but not limited to \u201carchitecture,\u201d \u201cdesign,\u201d \u201cdata flow,\u201d \u201ccontrol flow,\u201d \u201cexecution flow,\u201d\n\n\u201cany system in which You use NVIDIA GPUs to perform computations,\u201d \u201cconfiguration files,\u201d\n\n\u201cbuild files,\u201d \u201cdeployment files,\u201d \u201cruntime logs,\u201d and \u201cprofiler traces\u201d without providing additional\n\nidentifying or clarifying information to explain exactly what is sought; (11) it is improper because\n\nit is an interrogatory disguised as a document request; (12) given the definition of NVIDIA GPUs,\n\nthis request amounts to over 240 requests and thus is overbroad, unduly burdensome, and not\n\nproportional. Google further objects to this request to the extent that it seeks information protected\n\nby the attorney-client privilege, attorney work product doctrine, or any other applicable protection.\n\nGoogle further objects to this request as unduly burdensome to the extent it seeks documents that\n\nare over seven years old. Such documents, to the extent they exist, may reside in difficult-to-access\n\nsources. Google is not able to retrieve information from many of these sources, or even confirm\n\nwith certainty whether any responsive information in fact exists in the sources, without incurring\n\nsubstantial undue burden or cost.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\n\n -16-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 18 of 34\n\n\n\n\npresented. Google is willing to meet and confer regarding this request.\n\nREQUEST NO. 6:\n\n Documents sufficient to show whether computations You performed using NVIDIA GPUs\n\ninvolved artificial neural networks, neural-network computational layers or computations with\n\noutputs as inputs for other neurons or layers.\n\nRESPONSE TO REQUEST NO. 6:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad and vague as it is not reasonably limited or\n\ndiscernible in scope\u2014especially for a nonparty\u2014with its request for \u201ccomputations You performed\n\nusing NVIDIA GPUs\u201d involving \u201cartificial neural networks, neural-network computational layers\n\nor computations with outputs as inputs for other neurons or layers\u201d; (2) it is vague and ambiguous\n\nas to the phrases \u201cYou\u201d (see Objection 6 above), \u201cinvolved artificial neural networks, neural-\n\nnetwork computational layers or computations with outputs as inputs for other neurons or layers\u201d;\n\n(3) it seeks information that is not within Google\u2019s possession, custody or control; (4) it seeks\n\nelectronically stored information that is not reasonably accessible by Google without undue burden\n\nand/or cost; (5) it calls for information that Google is not capable of producing (or not reasonably\n\nable to produce); (6) it seeks information already in the possession of a party to the litigation; (7) it\n\nseeks information that is highly confidential, proprietary, that contains trade secrets, and/or is\n\nsubject to a confidentiality agreement or protective order; (8) it seeks information that is not\n\nproportionate to the needs of the case and not relevant to any party\u2019s claims or defenses; (9) it lacks\n\nrelevance, including but not limited to because this Request lacks a demonstrated nexus to the\n\nspecific patents-in-suit and the specific accused NVIDIA products and software; (10) it uses\n\n\n -17-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 19 of 34\n\n\n\n\noverbroad, vague and ambiguous terms and phrases in the request, including, but not limited to\n\n\u201cwhether computations You performed using NVIDIA GPUs involved,\u201d \u201cartificial neural\n\nnetworks,\u201d \u201cneural-network computational layers,\u201d \u201ccomputations with outputs as inputs for other\n\nneurons or layers\u201d without providing additional identifying or clarifying information to explain\n\nexactly what is sought; (11) it is improper because it is an interrogatory disguised as a document\n\nrequest; (12) given the definition of NVIDIA GPUs, this request amounts to over 240 requests and\n\nthus is overbroad, unduly burdensome, and not proportional. Google further objects to this request\n\nto the extent that it seeks information protected by the attorney-client privilege, attorney work\n\nproduct doctrine, or any other applicable protection. Google further objects to this request as unduly\n\nburdensome to the extent it seeks documents that are over seven years old. Such documents, to the\n\nextent they exist, may reside in difficult-to-access sources. Google is not able to retrieve information\n\nfrom many of these sources, or even confirm with certainty whether any responsive information in\n\nfact exists in the sources, without incurring substantial undue burden or cost.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\nREQUEST NO. 7:\n\n Documents sufficient to show whether You use a pointer to data stored in memory (e.g.\n\nmemory bank or partition), using as an input to a subsequent computational layer the pointer to\n\noutput data from a GPU computation, using pointers in neural network computations, swapping an\n\ninput pointer with the pointer to data output from a GPU computation, pointer swapping, pointer\n\nrotation, buffer swapping, ping-pong buffers, double or triple buffering, alternating input/output\n\nbuffers, or any other technique in which output data from one computation, layer, iteration, time\n\nstep, or cycle becomes input data for a later computation, layer, iteration, time step, or cycle.\n\n\n -18-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 20 of 34\n\n\n\n\nRESPONSE TO REQUEST NO. 7:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad and vague as it is not reasonably limited or\n\ndiscernible in scope\u2014especially for a nonparty\u2014with its request enumerating a long list of memory\n\nmanagement techniques\u2014pointer swapping, buffer swapping, ping-pong buffers, double or triple\n\nbuffering, and others\u2014and then adding a catch-all for \u201cany other technique\u201d by which GPU output\n\nbecomes input to a later computation, a catch-all is so broad that it would encompass virtually any\n\niterative GPU computation, and would require Google to review and analyze the entirety of its\n\nsource code repositories spanning the breadth of Google\u2019s computing infrastructure and product\n\nportfolio for responsive information; (2) it is vague and ambiguous as to the phrases \u201cYou\u201d (see\n\nObjection 6 above), \u201cuse a pointer to data stored in memory (e.g. memory bank or partition), using\n\nas an input to a subsequent computational layer the pointer to output data from a GPU computation,\n\nusing pointers in neural network computations, swapping an input pointer with the pointer to data\n\noutput from a GPU computation, pointer swapping, pointer rotation, buffer swapping, ping-pong\n\nbuffers, double or triple buffering, alternating input/output buffers, or any other technique in which\n\noutput data from one computation, layer, iteration, time step, or cycle becomes input data for a later\n\ncomputation, layer, iteration, time step, or cycle\u201d; (3) it seeks information that is not within Google\u2019s\n\npossession, custody or control; (4) it seeks electronically stored information that is not reasonably\n\naccessible by Google without undue burden and/or cost; (5) it calls for information that Google is\n\nnot capable of producing (or not reasonably able to produce); (6) it seeks information already in the\n\npossession of a party to the litigation; (7) it seeks information that is highly confidential, proprietary,\n\nthat contains trade secrets, and/or is subject to a confidentiality agreement or protective order; (8) it\n\n\n -19-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 21 of 34\n\n\n\n\nseeks information that is not proportionate to the needs of the case and not relevant to any party\u2019s\n\nclaims or defenses; (9) it lacks relevance, including but not limited to because this Request lacks a\n\ndemonstrated nexus to the specific patents-in-suit and the specific accused NVIDIA products and\n\nsoftware; (10) it uses overbroad, vague and ambiguous terms and phrases in the request, including,\n\nbut not limited to \u201cwhether You use a pointer to data stored in memory (e.g. memory bank or\n\npartition),\u201d \u201cusing as an input to a subsequent computational layer the pointer to output data from a\n\nGPU computation,\u201d \u201cusing pointers in neural network computations,\u201d \u201cswapping an input pointer\n\nwith the pointer to data output from a GPU computation,\u201d \u201cpointer swapping,\u201d \u201cpointer rotation,\u201d\n\n\u201cbuffer swapping,\u201d \u201cping-pong buffers,\u201d \u201cdouble or triple buffering,\u201d \u201calternating input/output\n\nbuffers,\u201d or \u201cany other technique in which output data from one computation, layer, iteration, time\n\nstep, or cycle becomes input data for a later computation, layer, iteration, time step, or cycle\u201d without\n\nproviding additional identifying or clarifying information to explain exactly what is sought; (11) it\n\nis improper because it is an interrogatory disguised as a document request; (12) given the definition\n\nof NVIDIA GPUs, this request amounts to over 240 requests and thus is overbroad, unduly\n\nburdensome, and not proportional. Google further objects to this request to the extent that it seeks\n\ninformation protected by the attorney-client privilege, attorney work product doctrine, or any other\n\napplicable protection. Google further objects to this request as unduly burdensome to the extent it\n\nseeks documents that are over seven years old. Such documents, to the extent they exist, may reside\n\nin difficult-to-access sources. Google is not able to retrieve information from many of these sources,\n\nor even confirm with certainty whether any responsive information in fact exists in the sources,\n\nwithout incurring substantial undue burden or cost.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\n\n -20-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 22 of 34\n\n\n\n\nREQUEST NO. 8:\n\n Documents sufficient to show whether You store input data, output data, intermediate\n\nresults, tensors, activations, weights, parameters, internal variables, GPU programs, kernels,\n\ntextures, shaders, or other GPU-computation-related data in separate, partitioned, logical, physical,\n\nfirst/second, input/output, texture, shader, shared, global, device, host, pinned, GPU RAM, GPU\n\ncache(s), or unified memory regions (shared by CPU and GPU) when performing computations\n\nusing NVIDIA GPUs.\n\nRESPONSE TO REQUEST NO. 8:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad and vague as it is not reasonably limited or\n\ndiscernible in scope\u2014especially for a nonparty\u2014with its request for information about how Google\n\nmanages GPU memory across an extensive list of memory types and data categories that spans\n\nessentially every aspect of GPU computation and would require Google to review and analyze the\n\nentirety of its source code repositories spanning the breadth of Google\u2019s computing infrastructure\n\nand product portfolio for responsive information; (2) it is vague and ambiguous as to the phrases\n\n\u201cYou\u201d (see Objection 6 above), \u201cstore input data, output data, intermediate results, tensors,\n\nactivations, weights, parameters, internal variables, GPU programs, kernels, textures, shaders, or\n\nother GPU-computation-related data in separate, partitioned, logical, physical, first/second,\n\ninput/output, texture, shader, shared, global, device, host, pinned, GPU RAM, GPU cache(s), or\n\nunified memory regions (shared by CPU and GPU) when performing computations\u201d; (3) it seeks\n\ninformation that is not within Google\u2019s possession, custody or control; (4) it seeks electronically\n\nstored information that is not reasonably accessible by Google without undue burden and/or cost;\n\n\n -21-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 23 of 34\n\n\n\n\n(5) it calls for information that Google is not capable of producing (or not reasonably able to\n\nproduce); (6) it seeks information already in the possession of a party to the litigation; (7) it seeks\n\ninformation that is highly confidential, proprietary, that contains trade secrets, and/or is subject to a\n\nconfidentiality agreement or protective order; (8) it seeks information that is not proportionate to\n\nthe needs of the case and not relevant to any party\u2019s claims or defenses, as it seeks information about\n\nGoogle\u2019s systems that use NVIDIA GPUs, not limited to the functionality of the NVIDIA GPUs\n\nthemselves; (9) it lacks relevance, including but not limited to because this Request lacks a\n\ndemonstrated nexus to the specific patents-in-suit and the specific accused NVIDIA products and\n\nsoftware; (10) it uses overbroad, vague and ambiguous terms and phrases in the request, including,\n\nbut not limited to \u201cstore input data,\u201d \u201cintermediate results,\u201d \u201ctensors,\u201d \u201cactivations,\u201d \u201cweights,\u201d\n\n\u201cparameters,\u201d \u201cinternal variables,\u201d \u201cGPU programs,\u201d \u201ckernels,\u201d \u201ctextures,\u201d \u201cshaders,\u201d \u201cother GPU-\n\ncomputation-related data in separate, partitioned, logical, physical, first/second, input/output,\n\ntexture, shader, shared, global, device, host, pinned, GPU RAM, GPU cache(s), or unified memory\n\nregions (shared by CPU and GPU) when performing computations using NVIDIA GPUs,\u201d without\n\nproviding additional identifying or clarifying information to explain exactly what is sought; (11) it\n\nis improper because it is an interrogatory disguised as a document request; (12) given the definition\n\nof NVIDIA GPUs, this request amounts to over 240 requests and thus is overbroad, unduly\n\nburdensome, and not proportional. Google further objects to this request to the extent that it seeks\n\ninformation protected by the attorney-client privilege, attorney work product doctrine, or any other\n\napplicable protection. Google further objects to this request as unduly burdensome to the extent it\n\nseeks documents that are over seven years old. Such documents, to the extent they exist, may reside\n\nin difficult-to-access sources. Google is not able to retrieve information from many of these sources,\n\nor even confirm with certainty whether any responsive information in fact exists in the sources,\n\n\n -22-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 24 of 34\n\n\n\n\nwithout incurring substantial undue burden or cost.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\nREQUEST NO. 9:\n\n Documents sufficient to show how input data is received, acquired, stored, transferred,\n\ncopied, streamed, prefetched, staged, queued, or loaded from CPU memory, host memory, system\n\nmemory, storage, sensors, cameras, or other input sources to NVIDIA GPU memory \u2013 including\n\nGPU RAM (e.g. GPU HBM, GDDR) and/or GPU cache(s) \u2013 before, during, or in parallel with\n\ncomputations You perform using NVIDIA GPUs.\n\nRESPONSE TO REQUEST NO. 9:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a nonparty\u2014with its request for information about Google\u2019s internal data\n\npipeline architecture at the level of GPU memory transfer operations that would require Google to\n\nreview and analyze the entirety of its source code repositories spanning the breadth of Google\u2019s\n\ncomputing infrastructure and product portfolio for responsive information; (2) it is vague and\n\nambiguous as to the phrases \u201cYou\u201d (see Objection 6 above), \u201chow input data is received, acquired,\n\nstored, transferred, copied, streamed, prefetched, staged, queued, or loaded from CPU memory, host\n\nmemory, system memory, storage, sensors, cameras, or other input sources to NVIDIA GPU\n\nmemory\u201d; (3) it seeks information that is not within Google\u2019s possession, custody or control; (4) it\n\nseeks electronically stored information that is not reasonably accessible by Google without undue\n\nburden and/or cost; (5) it calls for information that Google is not capable of producing (or not\n\n\n -23-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 25 of 34\n\n\n\n\nreasonably able to produce); (6) it seeks information already in the possession of a party to the\n\nlitigation; (7) it seeks information that is highly confidential, proprietary, that contains trade secrets,\n\nand/or is subject to a confidentiality agreement or protective order; (8) it seeks information that is\n\nnot proportionate to the needs of the case and not relevant to any party\u2019s claims or defenses, as it\n\nseeks information about Google\u2019s systems that interact with NVIDIA GPUs, not limited to the\n\nfunctionality of the NVIDIA GPUs themselves; (9) it lacks relevance, including but not limited to\n\nbecause this Request lacks a demonstrated nexus to the specific patents-in-suit and the specific\n\naccused NVIDIA products and software; (10) it uses overbroad, vague and ambiguous terms and\n\nphrases in the request, including, but not limited to \u201chow input data is received, acquired, stored,\n\ntransferred, copied, streamed, prefetched, staged, queued, or loaded from CPU memory, host\n\nmemory, system memory, storage, sensors, cameras, or other input sources to NVIDIA GPU\n\nmemory \u2013 including GPU RAM (e.g. GPU HBM, GDDR) and/or GPU cache(s),\u201d \u201cbefore, during,\n\nor in parallel with computations You perform using NVIDIA GPUs\u201d without providing additional\n\nidentifying or clarifying information to explain exactly what is sought; (11) it is improper because\n\nit is an interrogatory disguised as a document request; (12) given the definition of NVIDIA GPUs,\n\nthis request amounts to over 240 requests and thus is overbroad, unduly burdensome, and not\n\nproportional. Google further objects to this request to the extent that it seeks information protected\n\nby the attorney-client privilege, attorney work product doctrine, or any other applicable protection.\n\nGoogle further objects to this request as unduly burdensome to the extent it seeks documents that\n\nare over seven years old. Such documents, to the extent they exist, may reside in difficult-to-access\n\nsources. Google is not able to retrieve information from many of these sources, or even confirm\n\nwith certainty whether any responsive information in fact exists in the sources, without incurring\n\nsubstantial undue burden or cost.\n\n\n -24-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 26 of 34\n\n\n\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\nREQUEST NO. 10:\n\n Documents sufficient to show how output data from a GPU computation(s), intermediate\n\nresults of GPU computations, tensors, buffers, activations, variables, or other computation results\n\nare stored, transferred, copied, streamed, written back, returned, accumulated, reused, or made\n\navailable including asynchronously from NVIDIA GPU memory to CPU memory, host memory,\n\nsystem memory, storage, display, network, or another memory location before, during, or in parallel\n\nwith computations You perform using NVIDIA GPUs \u2013 and also including in the opposite direction,\n\ncopying data from CPU or host or other memory to a queue for GPU computation while other GPU\n\ncomputations are occurring.\n\nRESPONSE TO REQUEST NO. 10:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad for the same reasons as stated in response to\n\nRequest No. 9\u2014the Request covers essentially the reverse data flow (GPU memory to CPU/host\n\nmemory) as well as bidirectional concurrent data movement\u2014effectively seeking a complete\n\ntechnical map of Google\u2019s GPU computation data pipeline; (2) this Request, combined with\n\nRequests Nos. 7, 8, and 9, collectively amount to a comprehensive demand for Google's entire GPU\n\ncomputing architecture and implementation, which is disproportionate given Google's status as a\n\nthird-party customer; (3) it is vague and ambiguous as to the phrases \u201cYou\u201d (see Objection 6 above),\n\n\u201chow output data from a GPU computation(s), intermediate results of GPU computations, tensors,\n\nbuffers, activations, variables, or other computation results are stored, transferred, copied, streamed,\n\n\n -25-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 27 of 34\n\n\n\n\nwritten back, returned, accumulated, reused, or made available including asynchronously from\n\nNVIDIA GPU memory to CPU memory, host memory, system memory, storage, display, network,\n\nor another memory location before, during, or in parallel with computations You perform using\n\nNVIDIA GPUs \u2013 and also including in the opposite direction, copying data from CPU or host or\n\nother memory to a queue for GPU computation while other GPU computations are occurring\u201d; (4)\n\nit seeks information that is not within Google\u2019s possession, custody or control; (5) it seeks\n\nelectronically stored information that is not reasonably accessible by Google without undue burden\n\nand/or cost; (6) it calls for information that Google is not capable of producing (or not reasonably\n\nable to produce); (7) it seeks information already in the possession of a party to the litigation; (8) it\n\nseeks information that is highly confidential, proprietary, that contains trade secrets, and/or is\n\nsubject to a confidentiality agreement or protective order; (9) it seeks information that is not\n\nproportionate to the needs of the case and not relevant to any party\u2019s claims or defenses, as it seeks\n\ninformation about Google\u2019s systems that interact with NVIDIA GPUs, not limited to the\n\nfunctionality of the NVIDIA GPUs themselves; (10) it lacks relevance, including but not limited to\n\nbecause this Request lacks a demonstrated nexus to the specific patents-in-suit and the specific\n\naccused NVIDIA products and software; (11) it uses overbroad, vague and ambiguous terms and\n\nphrases in the request, including, but not limited to \u201chow output data from a GPU computation(s),\n\nintermediate results of GPU computations, tensors, buffers, activations, variables, or other\n\ncomputation results are stored, transferred, copied, streamed, written back, returned, accumulated,\n\nreused, or made available including asynchronously from NVIDIA GPU memory to CPU memory,\n\nhost memory, system memory, storage, display, network,\u201d \u201canother memory location,\u201d \u201cbefore,\n\nduring, or in parallel with computations You perform using NVIDIA GPUs,\u201d \u201cin the opposite\n\ndirection, copying data from CPU or host or other memory to a queue for GPU computation while\n\n\n -26-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 28 of 34\n\n\n\n\nother computations are occurring\u201d without providing additional identifying or clarifying information\n\nto explain exactly what is sought; (12) it is improper because it is an interrogatory disguised as a\n\ndocument request; (13) given the definition of NVIDIA GPUs, this request amounts to over 240\n\nrequests and thus is overbroad, unduly burdensome, and not proportional. Google further objects\n\nto this request to the extent that it seeks information protected by the attorney-client privilege,\n\nattorney work product doctrine, or any other applicable protection. Google further objects to this\n\nrequest as unduly burdensome to the extent it seeks documents that are over seven years old. Such\n\ndocuments, to the extent they exist, may reside in difficult-to-access sources. Google is not able to\n\nretrieve information from many of these sources, or even confirm with certainty whether any\n\nresponsive information in fact exists in the sources, without incurring substantial undue burden or\n\ncost.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\nREQUEST NO. 11:\n\n Documents sufficient to show how computations You perform using NVIDIA GPUs are\n\nscheduled, ordered, controlled, queued, synchronized, parallelized, launched, interrupted, resumed,\n\nor executed, including through kernels, CUDA streams, CUDA graphs, events, threads, controllers,\n\nschedulers, compilers, runtimes, inference engines, run lists, run engines, or custom software.\n\nRESPONSE TO REQUEST NO. 11:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a nonparty\u2014with its request for information about how Google\u2019s internal\n\n\n -27-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 29 of 34\n\n\n\n\nscheduling and execution infrastructure interfaces with NVIDIA GPU hardware across all of\n\nGoogle\u2019s GPU-utilizing systems; the Request is an open-ended enumeration of scheduling and\n\nexecution mechanisms, combined with the catch-all \u201cor custom software,\u201d which renders the\n\nRequest's scope unlimited (2) it is vague and ambiguous as to the phrases \u201cYou\u201d (see Objection 6\n\nabove), \u201chow computations You perform using NVIDIA GPUs are scheduled, ordered, controlled,\n\nqueued, synchronized, parallelized, launched, interrupted, resumed, or executed\u201d; (3) it seeks\n\ninformation that is not within Google\u2019s possession, custody or control; (4) it seeks electronically\n\nstored information that is not reasonably accessible by Google without undue burden and/or cost;\n\n(5) it calls for information that Google is not capable of producing (or not reasonably able to\n\nproduce); (6) it seeks information already in the possession of a party to the litigation\u2014e.g., it seeks\n\ninformation about how NVIDIA\u2019s own CUDA runtime, CUDA streams, CUDA graphs, and related\n\ntools function, that information is more appropriately sought from NVIDIA itself; (7) it seeks\n\ninformation that is highly confidential, proprietary, that contains trade secrets, and/or is subject to a\n\nconfidentiality agreement or protective order; (8) it seeks information that is not proportionate to\n\nthe needs of the case and not relevant to any party\u2019s claims or defenses, as it seeks information about\n\nGoogle\u2019s systems that interact with NVIDIA GPUs, not limited to the functionality of the NVIDIA\n\nGPUs themselves; (9) it lacks relevance, including but not limited to because this Request lacks a\n\ndemonstrated nexus to the specific patents-in-suit and the specific accused NVIDIA products and\n\nsoftware; (10) it uses overbroad, vague and ambiguous terms and phrases in the request, including,\n\nbut not limited to \u201chow computations You perform using NVIDIA GPUs are scheduled, ordered,\n\ncontrolled, queued, synchronized, parallelized, launched, interrupted, resumed, or executed,\u201d\n\n\u201cthrough kernels, CUDA streams, CUDA graphs, events, threads, controllers, schedulers, compilers,\n\nruntimes, inference engines, run lists, run engines,\u201d \u201ccustom software\u201d without providing additional\n\n\n -28-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 30 of 34\n\n\n\n\nidentifying or clarifying information to explain exactly what is sought; (11) it is improper because\n\nit is an interrogatory disguised as a document request; (12) given the definition of NVIDIA GPUs,\n\nthis request amounts to over 240 requests and thus is overbroad, unduly burdensome, and not\n\nproportional. Google further objects to this request to the extent that it seeks information protected\n\nby the attorney-client privilege, attorney work product doctrine, or any other applicable protection.\n\nGoogle further objects to this request as unduly burdensome to the extent it seeks documents that\n\nare over seven years old. Such documents, to the extent they exist, may reside in difficult-to-access\n\nsources. Google is not able to retrieve information from many of these sources, or even confirm\n\nwith certainty whether any responsive information in fact exists in the sources, without incurring\n\nsubstantial undue burden or cost.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\nREQUEST NO. 12:\n\n Documents sufficient to show whether and how user inputs, user commands, configuration\n\nchanges, parameter changes, model changes, computational-element changes, input changes,\n\ninterruptions, or display/output changes affect computations You perform using NVIDIA GPUs\n\nand/or queue them for GPU computation.\n\nRESPONSE TO REQUEST NO. 12:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this request on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a nonparty\u2014with the Request encompassing any way in which user\n\ninteractions or configuration changes affect GPU computations\u2014a description that could apply to\n\n\n -29-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 31 of 34\n\n\n\n\nvirtually any consumer-facing or developer-facing product that runs on GPU infrastructure; (2) it\n\noverlaps substantially with Requests Nos. 7 through 11 and, in combination, these Requests\n\ncollectively seek a complete technical disclosure of Google\u2019s GPU computing infrastructure; (3) it\n\nis vague and ambiguous as to the phrases \u201cYou\u201d (see Objection 6 above), \u201chow user inputs, user\n\ncommands, configuration changes, parameter changes, model changes, computational-element\n\nchanges, input changes, interruptions, or display/output changes affect computations You perform\n\nusing NVIDIA GPUs and/or queue them for GPU computation\u201d; (4) it seeks information that is not\n\nwithin Google\u2019s possession, custody or control; (5) it seeks electronically stored information that is\n\nnot reasonably accessible by Google without undue burden and/or cost; (6) it calls for information\n\nthat Google is not capable of producing (or not reasonably able to produce); (7) it seeks information\n\nalready in the possession of a party to the litigation; (8) it seeks information that is highly\n\nconfidential, proprietary, that contains trade secrets, and/or is subject to a confidentiality agreement\n\nor protective order; (9) it seeks information that is not proportionate to the needs of the case and not\n\nrelevant to any party\u2019s claims or defenses, as it seeks information about Google\u2019s systems that\n\ninteract with NVIDIA GPUs, not limited to the functionality of the NVIDIA GPUs themselves; (10)\n\nit lacks relevance, including but not limited to because this Request lacks a demonstrated nexus to\n\nthe specific patents-in-suit and the specific accused NVIDIA products and software; (11) it uses\n\noverbroad, vague and ambiguous terms and phrases in the request, including, but not limited to \u201chow\n\nuser inputs, user commands, configuration changes, parameter changes, model changes,\n\ncomputational-element changes, input changes, interruptions, or display/output changes affect\n\ncomputations You perform using NVIDIA GPUs and/or queue them for GPU computation\u201d without\n\nproviding additional identifying or clarifying information to explain exactly what is sought; (12) it\n\nis improper because it is an interrogatory disguised as a document request; (13) given the definition\n\n\n -30-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 32 of 34\n\n\n\n\nof NVIDIA GPUs, this request amounts to over 240 requests and thus is overbroad, unduly\n\nburdensome, and not proportional. Google further objects to this request to the extent that it seeks\n\ninformation protected by the attorney-client privilege, attorney work product doctrine, or any other\n\napplicable protection. Google further objects to this request as unduly burdensome to the extent it\n\nseeks documents that are over seven years old. Such documents, to the extent they exist, may reside\n\nin difficult-to-access sources. Google is not able to retrieve information from many of these sources,\n\nor even confirm with certainty whether any responsive information in fact exists in the sources,\n\nwithout incurring substantial undue burden or cost.\n\n Accordingly, Google will not produce documents in response to this request as currently\n\npresented. Google is willing to meet and confer regarding this request.\n\n\n\n\nDated: July 21, 2026 WILSON SONSINI GOODRICH & ROSATI\n Professional Corporation\n\n By: /s/ Jordan R. Jaffe\n Jordan R. Jaffe\n\n Attorney for Respondent\n Google LLC\n\n\n\n\n -31-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 33 of 34\n\n\n\n\n PROOF OF SERVICE\n\n I, Mercedes McKone, declare:\n\n I am employed in the County of San Francisco, in the State of California. I am over the age\n\nof 18 years and not a party to the within action. My business address is Wilson Sonsini Goodrich\n\n& Rosati, P.C., 12235 El Camino Real, San Diego, California, 92130.\n\n On this date, I served:\n\nNONPARTY GOOGLE LLC\u2019S OBJECTIONS AND RESPONSES TO NEURAL AI, LLC\u2019S\n SUBPOENA TO PRODUCE DOCUMENTS, INFORMATION, OR OBJECTS\n\n \u2612 By forwarding the document(s) by electronic transmission on this date to the Internet\n\nemail address(es) listed below:\n\n Max L. Tribble, Esq. Tamar Lusztig, Esq.\n Brian D. Melton, Esq. Emily Portuguese, Esq.\n Rocco Magni, Esq. SUSMAN GODFREY L.L.P.\n Samuel Drezdzon, Esq. One Manhattan West, 50th Floor\n SUSMAN GODFREY L.L.P. New York, NY 10001\n 1000 Louisiana, Suite 5100 tlusztig@susmangodfrey.com\n Houston, TX 77002 eportuguese@susmangodfrey.com\n mtribble@susmangodfrey.com\n bmelton@susmangodfrey.com Mark D. Siegmund, Esq.\n rmagni@susmangodfrey.com CHERRY JOHNSON SIEGMUND JAMES PC\n sdrezdzon@susmangodfrey.com Bridgeview Center\n 7901 Fish Pond Road, 2nd Floor\n Tanner Laiche Waco, TX 76710\n SUSMAN GODFREY L.L.P. msiegmund@cjsjlaw.com\n 401 Union Street, Suite 3000\n Seattle, WA 98101 Attorneys for Plaintiff\n tlaiche@susmangodfrey.com NEURAL AI, LLC\n\n Max Ciccarelli\n CICCARELLI LAW FIRM LLC\n 100 N. 6th Street, Suite 502\n Waco, Texas 76701\n max@ciccarellilawfirm.com\n\n\n\n\n -1-\n\f Case 7:26-mc-00324-DC Document 1-10 Filed 08/18/26 Page 34 of 34\n\n\n\n\n I declare under penalty of perjury under the laws of the State of California that the foregoing\n\nis true and correct. Executed at San Diego, California on July 21, 2026.\n\n\n __________________________________\n Mercedes McKone\n\n\n\n\n -2-\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:17.916076-07:00","document_number":"1","attachment_number":10,"pacer_doc_id":"181037219905","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 9","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514524/","id":490514524,"tags":[],"absolute_url":"/docket/74667129/1/11/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.101408-07:00","date_modified":"2026-08-23T08:26:23.548529-07:00","sha1":"dd655005487f6eb7fb35c0b22f5195ab8cc2f32c","page_count":18,"file_size":225880,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.11.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.11.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 1 of 18\n\n\n\n\n EXHIBIT\n\n 10\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 2 of 18\n\n\n\n\n IN THE UNITED STATES DISTRICT COURT\n WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\n\nNEURAL AI, LLC,\n\n Plaintiff, Civil Action No. 7:24-cv-00221-ADA-DTG\n\n v.\n\nNVIDIA CORPORATION,\n\n Defendant.\n\n\n RESPONSES AND OBJECTIONS OF NONPARTY GOOGLE LLC\n TO SUBPOENA TO TESTIFY AT A DEPOSITION IN A CIVIL ACTION\n\n Pursuant to Federal Rule of Civil Procedure 45 (\u201cRule 45\u201d), nonparty Google LLC\n\n(\u201cGoogle\u201d) makes the following responses and objections to the June 24, 2026 Subpoena to Testify\n\nat a Deposition in a Civil Action served by Neural AI, LLC (\u201cNeural AI\u201d) (the \u201cSubpoena\u201d).\n\n PRELIMINARY STATEMENT\n\n Google responds to the Subpoena subject to the accompanying objections. Google is a non-\n\nparty to this matter, is not involved in the underlying dispute, and has not otherwise engaged in\n\ndiscovery with the parties. All of the responses contained herein, therefore, are based only upon\n\nsuch limited information and documents as are presently available to and specifically known to\n\nGoogle. The following responses are given without prejudice to Google\u2019s right to produce any\n\nsubsequently discovered information or facts that Google may discover. Google, accordingly,\n\nreserves the right to change any and all responses herein if additional facts are ascertained, analyses\n\nare made, research is completed, or contentions are made.\n\n GENERAL OBJECTIONS\n\n The following General Objections apply to and are incorporated by reference into each of\n\n\n\n -1-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 3 of 18\n\n\n\n\nthe specific responses and objections set forth below, as if fully set forth therein. Google\u2019s assertion\n\nof any specific objection in response to a particular Request does not waive any General Objection.\n\nGoogle reserves the right to supplement, amend, or correct these responses and objections as\n\nadditional information becomes available.\n\n 1. Obligations in Excess of Federal Rules. Google objects to the Subpoena\u2019s\n\ndefinitions and instructions to the extent they purport to impose obligations on Google in excess of\n\nany applicable federal or state codes of civil procedure, rules of evidence, or any other applicable\n\nlaw. As set forth in the following objections and responses to the Subpoena and its request for a\n\ndeposition of a Google witness, Google will not provide a witness to testify or appear for the\n\nscheduled deposition because the deposition request is unduly burdensome and unnecessary.\n\nFurther, it is improper to require Google, who is a non-party, to produce a witness to provide\n\ndeposition testimony on subject matters and information that could be obtained from another\n\nsource, such as documents and other non-testimonial sources of information.\n\n 2. Improper place of compliance. Google objects to this Subpoena to the extent the\n\nplace of compliance\u2014Planet Depos, Downtown Austin, 100 Congress Ave., Ste. 2000, Austin,\n\nTX 78701\u2014does not satisfy Rule 45(c)(2)(A) of the Federal Rules of Civil Procedure. Rule 45\n\npermits production of a witness for deposition \u201cat a place within 100 miles of where the person\n\nresides, is employed, or regularly transacts business in person.\u201d The relevant inquiry under Rule\n\n45 is not simply whether Google has some business presence anywhere within 100 miles of the\n\nspecified location, but whether the custodians of records whose files would be responsive to the\n\nSubpoena reside, are employed, or regularly transact business in person within 100 miles of the\n\ndesignated compliance location. Google\u2019s principal place of business is in Mountain View,\n\nCalifornia, and the employees most knowledgeable about and in possession of documents\n\n\n -2-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 4 of 18\n\n\n\n\nresponsive to the Requests would be located in or near Google's headquarters, not in Austin,\n\nTexas. Google also objects to the time and place set by the Subpoena for the deposition because\n\nthey were selected unilaterally, without consulting with Google about the availability of its\n\nwitness(es) or its counsel. To the extent Google produces a witness to provide deposition\n\ntestimony in response to the Subpoena, Google shall do so at a mutually agreeable time and place.\n\nNotwithstanding this objection, and without waiving it, Google responds as set forth below to\n\npreserve a cooperative record.\n\n 3. Undue Burden on a Non-Party. Google objects to the Subpoena on the grounds\n\nthat it seeks to impose an undue burden on Google, which is not a party to the underlying action.\n\nGoogle further objects to the Subpoena to the extent it seeks documents or information that is in\n\nthe possession, custody, or control of a party to the underlying action, such as NVIDIA\n\nCorporation, or equally available from another source (including public sources) that is more\n\nconvenient, less burdensome, or less expensive than requiring Google to produce such documents\n\nor information. As a disinterested non-party, Google should not be subjected to the burden of\n\nsearching for and producing such documents or information unless and until all reasonable means\n\nof obtaining that information directly from such other sources have been exhausted.\n\n 4. Unreasonable Search/Investigation. Google objects to the Subpoena to the extent\n\nit purports to require Google to perform anything more than a reasonable and diligent\n\ninvestigation from reasonably accessible sources. Google specifically objects to any Request that\n\nrequires the collection, review, and production of emails or other internal communications as\n\nfacially overbroad and unduly burdensome on a non-party.\n\n 5. Overbreadth and Lack of Proportionality. Google objects to the Subpoena to\n\nthe extent it seeks information that is not proportionate to the needs of the case or not relevant to\n\n\n -3-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 5 of 18\n\n\n\n\nany party\u2019s claims or defenses. Moreover, because neither a copy of the underlying complaint nor\n\na description of the underlying claims at issue accompanied the Subpoena, Google is unable to\n\ndiscern whether the documents or information sought by the Subpoena are discoverable, and what\n\nits obligations are, if any, to respond to the Subpoena. Google objects to each Request to the\n\nextent it is overly broad, seeks information that is not relevant to the claims or defenses in the\n\nunderlying action, and is not proportional to the needs of the case as required by Fed. R. Civ. P.\n\n26(b)(1). The definition of \u201cNVIDIA GPUs\u201d alone spans three full pages and encompasses\n\ndozens of GPU architectures and hundreds of individual GPU products covering nearly a decade\n\nof product generations. Requests defined in terms of this expansive definition\u2014and further\n\nqualified by omnibus definitions equating \u201cor\u201d with \u201cand\u201d and \u201cany\u201d with \u201call\u201d\u2014are facially\n\noverbroad. Google also objects to the Requests as overly broad and unduly burdensome to the\n\nextent they seek \u201cAll Documents\u201d or \u201cAll Communications\u201d with respect to a subject because\n\nsuch omnibus requests seek discovery that is not relevant to a party\u2019s claim or defense and are not\n\nproportional to the needs of the case.\n\n 6. Vague, Overbreadth, and Lack of Proportionality. Google objects to the\n\ndefinition of \u201cNVIDIA GPUs,\u201d which alone spans three full pages and encompasses dozens of\n\nGPU architectures and hundreds of individual GPU products. Requests defined in terms of this\n\nexpansive definition\u2014and further qualified by omnibus definitions equating \u201cor\u201d with \u201cand\u201d and\n\n\u201cany\u201d with \u201call\u201d\u2014are facially overbroad. Google objects to the definition of \u201cNVIDIA GPU\u201d as\n\nvague, overbroad, unduly burdensome and disproportionate to the needs of the case to the extent it\n\nincludes over 240 different devices in addition to \u201cany and all variations of the aforementioned\n\nproducts (including at least products having different options for number of GPUs.\u201d Google also\n\nobjects to this definition as unduly burdensome and disproportionate to the needs of the case to the\n\n\n -4-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 6 of 18\n\n\n\n\nextent it purports to require Google to determine what specific products fall within plaintiff\u2019s\n\ndefinition. Google will not attempt to interpret this term. Google objects to this definition to the\n\nextent it requires an expert or legal opinion. Google also objects to Instruction No. 23, which uses\n\nthe terms \u201cNVIDIA GPU-Acceleration Hardware\u201d and \u201cNVIDIA GPU-Acceleration Software,\u201d\n\nbut nowhere are those terms defined. Google will not attempt to interpret these terms. Google\n\nalso objects to Instruction No. 34, which uses the terms \u201cNVIDIA Hardware\u201d and \u201cNVIDIA\n\nSoftware,\u201d but nowhere are those terms defined, and hence they are vague, overbroad, and unduly\n\nburdensome. Google will not attempt to interpret these terms.\n\n Google also objects to the definition of \u201cSource Code\u201d as vague, overbroad, unduly\n\nburdensome, and disproportionate to the needs of the case. The definition purports to encompass\n\nnot only human-readable programming instructions but also \u201call comments, annotations,\n\ndeclarations, functions, classes, and other components used to define the behavior of a software\n\nprogram,\u201d \u201call associated files necessary to understand, compile, and execute the code, such as\n\nscripts, header files, makefiles, configuration files, and documentation,\u201d as well as \u201call versions and\n\nrevisions relevant to the time periods and subject matter described in each interrogatory.\u201d As\n\ndefined, \"Source Code\" effectively sweeps in Google\u2019s entire software development history for any\n\nsystem touching NVIDIA GPUs. Google also objects that \u201cnecessary to understand\u201d is vague and\n\nambiguous and subjective. Google further objects to this definition to the extent it seeks Source\n\nCode that constitutes Google's most sensitive trade secret and proprietary information. Compelling\n\na non-party to produce source code is an extraordinary measure that requires, at minimum, a\n\nshowing of substantial need\u201d that NAI has not made. Such production would also require entry of\n\na protective order providing source code-level protections\u2014which has not been established. Google\n\nwill not produce Source Code, as defined, absent such a showing and such protections. To the extent\n\n\n -5-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 7 of 18\n\n\n\n\nany specific Request incorporates this definition, Google objects to that Request on these same\n\ngrounds.\n\n Google also objects to the definitions of \u201cconcerning,\u201d \u201crelated to,\u201d and \u201cregarding\u201d\n\nencompass over a dozen different verbs in a deliberately all-inclusive formulation that renders\n\nvirtually any document potentially responsive to any Request. Google also objects to the\n\ndefinition of \u201cYou\u201d or \u201cYour\u201d as overbroad, unduly burdensome, and disproportionate to the\n\nneeds of the case. As defined, the terms purport to encompass not only Google LLC itself but also\n\nits predecessors, successors, parents, subsidiaries, divisions, affiliates, and all past or present\n\ndirectors, officers, partners, managers, employees, contractors, agents, representatives,\n\naccountants, consultants, in-house and outside counsel, and any other person or entity acting or\n\npurporting to act on its behalf or subject to its control. The definition further expressly extends to\n\nany Google parent, subsidiary, affiliate, or other related entity that has \u201cused, licensed, deployed,\n\nevaluated, or integrated NVIDIA GPUs or software.\u201d As defined, \u201cYou\u201d and \u201cYour\u201d would\n\nrequire Google conduct an unduly burdensome undertaking to determine who may fit into this\n\ndefinition, an then search for and produce documents from those source, including those not\n\nwithin Google LLC's own possession, custody, or control, and to undertake an investigation\n\nspanning entities and individuals that are legally distinct from Google LLC and over whose\n\ndocuments and information Google LLC may have no authority to collect or produce. Google\n\nfurther objects to this definition to the extent it purports to impose discovery obligations on\n\nGoogle\u2019s in-house and outside counsel, whose documents and communications are protected by\n\nthe attorney-client privilege and work product doctrine. Google further objects to the catch-all\n\nphrase \u201cany other person or entity acting or purporting to act on its behalf or subject to its control\u201d\n\n\n\n\n -6-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 8 of 18\n\n\n\n\nas vague, undefined, and potentially limitless in scope. Google will interpret \u201cYou\u201d and \u201cYour\u201d to\n\nrefer solely to Google LLC. Google will interpret each Request reasonably and in good faith.\n\n 7. Confidential and Proprietary Information. Google objects to the Subpoena to\n\nthe extent it seeks confidential financial, proprietary or trade secret information belonging to\n\nGoogle or a third party, or any other information subject to a confidentiality agreement, protective\n\norder or legal duty of non-disclosure (\u201cConfidential Information\u201d). Google will only produce\n\ninformation it deems confidential pursuant to a confidentiality agreement or protective order that it\n\nbelieves is suitable for the protection of its Confidential Information. Even if an adequate\n\nprotective order has been entered in the underlying action by the presiding court, Google will only\n\nprovide Confidential Information to the extent Google can do so consistent with its legal,\n\ncontractual and other confidentiality obligations. Google reserves the right to redact Confidential\n\nInformation belonging to Google or third parties, as well as information concerning irrelevant\n\nmatters.\n\n 8. Privilege. Google objects to the Subpoena to the extent it seeks information\n\nprotected by any privilege, including the attorney-client privilege, work product immunity\n\ndoctrine, common interest privilege, or any other applicable privilege, immunity, or restriction on\n\ndiscovery. Any disclosure of privileged information by Google in response to the Subpoena shall\n\nnot be deemed a waiver of any such privilege, and Google expressly requests that any party that\n\nreceives any such privileged information produced by Google immediately return and do not make\n\nuse of any produced privileged information.\n\n 9. Relevance to Underlying Claims. Google objects to each Request to the extent it\n\nlacks a demonstrated nexus to the patents-in-suit or to any specific claim of direct, indirect, or\n\ninduced infringement by NVIDIA. Google\u2019s internal use of any products has no necessary\n\n\n -7-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 9 of 18\n\n\n\n\nbearing on whether NVIDIA\u2019s products infringe NAI\u2019s patents. Mere customer status does not\n\nrender a non-party\u2019s internal documents, communications, or financial information relevant to a\n\npatent infringement suit against the manufacturer.\n\n 10. Temporal and Geographic Scope. Google objects to the unbounded temporal and\n\ngeographical scope to the extent it encompasses time periods or activities not relevant to the\n\nspecific claims and accused products at issue.\n\n 11. Unnecessary Authentication Testimony. Google objects to the Subpoena to the\n\nextent that it is seeking deposition testimony to authenticate records produced by Google. Such\n\ntestimony is unnecessary and unduly burdensome. In lieu of producing a witness to appear and\n\ntestify for the requested deposition, Google is willing to consider providing an affidavit that\n\nauthenticates any documents produced in response to the Subpoena as business records.\n\n 12. Date and Time of Compliance. Google objects to the date and time set for\n\ncompliance with the Subpoena as unreasonable, inconvenient, and unduly burdensome. The date\n\nand time were selected unilaterally by NAI without consulting Google or its counsel regarding\n\navailability, and without making any effort to identify a mutually agreeable time and place for\n\ncompliance. Google further objects that the time provided for compliance is insufficient to permit\n\nGoogle to conduct a reasonable and diligent investigation across its organization, identify\n\npotentially responsive information, and identify, prepare, and produce one or more knowledgeable\n\nwitnesses to testify competently on the noticed Topics. This is particularly true given the breadth\n\nand technical complexity of the Topics, which, as set forth in Google's specific objections below,\n\nimplicate highly sensitive and technically complex aspects of Google\u2019s computing infrastructure.\n\nTo the extent Google produces a witness in response to the Subpoenas, it will do so at a mutually\n\n\n\n\n -8-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 10 of 18\n\n\n\n\nagreeable date, time, and place to be negotiated with NAI's counsel following the parties\u2019 meet\n\nand confer.\n\n 13. Expenses. Google objects to the Subpoena on the grounds that it demands that\n\nGoogle produce a witness to provide deposition testimony at Google\u2019s own expense. To the extent\n\nthat Google produces a witness to provide deposition testimony in response to the Subpoena,\n\nGoogle shall only do so if properly compensated under applicable law for any costs, including\n\nattorney fees, incurred by Google and its witness(es) in connection with the deposition.\n\n 14. Google reserves the right to assert additional objections, or to supplement its\n\nobjections and responses as appropriate, particularly if any additional information regarding the\n\nSubpoena or the underlying claims at issue is provided.\n\n SPECIFIC RESPONSES AND OBJECTIONS TO THE DEPOSITION TOPICS\n\n Google incorporates each of its General Objections into each specific response below as if\n\nfully set forth therein. The assertion of a specific objection in any response does not waive any\n\nGeneral Objection. The Deposition Subpoena commands Google to designate one or more\n\nrepresentatives under Fed. R. Civ. P. 30(b)(6) to testify about the following Topics. Google objects\n\nto each Topic as set forth below. Google's conditional willingness to meet and confer about any\n\nTopic is not an admission that any witness can or will be prepared to testify on the full scope of the\n\nTopic as written, or that such testimony would be appropriate to compel from a non-party.\n\nTOPIC NO. 1:\n\n The NVIDIA software and libraries You use to perform computations, including but not\n\nlimited to NVIDIA\u2019s Aerial, Clara Parabricks, cuBLAS, cuDNN, cuFFT, cuQuantum, cuSOLVER,\n\ncuSPARSE, Drive, DriveWorks, Holoscan, Isaac, Isaac Lab, Maxine, Memory Map, Merlin,\n\n\n\n\n -9-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 11 of 18\n\n\n\n\nMetropolis, Modulus, Monai, Morpheus, NeMo, PyTorch, RAPIDS, Riva, Runtime Driver,\n\nTensorFlow, TensorRT, Triton, VSS (Deepstream).\n\nRESPONSE TO TOPIC NO. 1:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this topic on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a non-party\u2014as to its request for testimony about Google's use of more\n\nthan twenty named NVIDIA software products, and preparing one or more witnesses to testify\n\nabout Google\u2019s use of this broad list of software products across its entire computing\n\ninfrastructure would impose an extraordinary and unreasonable burden on a non-party; (2) it is\n\nvague and ambiguous, including but not limited to the phrases \u201cYou\u201d (see Objection 6 above),\n\n\u201csoftware and libraries You use to perform computations\u201d; (3) it seeks information that is not\n\nwithin Google\u2019s possession, custody or control or is within the possession of a party to the\n\nunderlying action, including because, e.g., it seeks information about NVIDIA software libraries\n\nthat are in NVIDIA\u2019s possession; (4) it seeks testimony that is highly confidential, proprietary,\n\nthat contains trade secrets, and/or is subject to a confidentiality agreement or protective order.\n\n Accordingly, Google will not produce a witness to appear and testify on this topic at the\n\ntime and place requested by the Subpoena but will consider a properly tailored request after the\n\nparties have met and conferred to discuss this request.\n\nTOPIC NO. 2:\n\n The NVIDIA sample Source Code You use, in whole or in part, to conduct computations.\n\n\n\n\n -10-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 12 of 18\n\n\n\n\nRESPONSE TO TOPIC NO. 2:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this topic on multiple grounds, including but not limited to the\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a non-party\u2014as to its request for testimony about \u201cNVIDIA sample\n\nSource Code\u201d without any meaningful limitation; (2) it is vague and ambiguous, including but not\n\nlimited to the phrases \u201cYou\u201d and \u201cSource Code\u201d (see Objection 6 above), \u201cNVIDIA sample\n\nSource Code,\u201d which is undefined and could encompass a vast range of publicly available and\n\nproprietary code distributed through various NVIDIA channels; (3) it seeks information that is not\n\nwithin Google\u2019s possession, custody or control or is within the possession of a party to the\n\nunderlying action, including because, e.g., it seeks information about NVIDIA software libraries\n\nthat are in NVIDIA\u2019s possession; (4) it seeks testimony that is highly confidential, proprietary,\n\nthat contains trade secrets, and/or is subject to a confidentiality agreement or protective order.\n\n Accordingly, Google will not produce a witness to appear and testify on this topic at the\n\ntime and place requested by the Subpoena but will consider a properly tailored request after the\n\nparties have met and conferred to discuss this request.\n\nTOPIC NO. 3:\n\n Your customizations and/or data inputs to NVIDIA software that alter the way in which\n\nNVIDIA software performs computations and/or a description of the data input to NVIDIA software\n\non which computations are run.\n\nRESPONSE TO TOPIC NO. 3:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this topic on multiple grounds, including but not limited to the\n\n\n -11-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 13 of 18\n\n\n\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a non-party\u2014as to its request for testimony about \u201ccustomizations and/or\n\ndata inputs that alter the way in which NVIDIA software performs computations and/or a\n\ndescription of the data input to NVIDIA software on which computations are run\u201d without any\n\nmeaningful limitation and asks Google to testify about every \u201ccustomization\u201d or \u201cdata input\u201d it\n\nhas made to any NVIDIA software product and the nature of all data inputs to such software\u2014an\n\ninquiry that could span the breadth of Google\u2019s computing infrastructure and product portfolio; (2)\n\nit is vague and ambiguous, including but not limited to the phrases \u201cYou\u201d and \u201cSource Code\u201d (see\n\nObjection 6 above), \u201cNVIDIA software,\u201d \u201ccustomizations,\u201d \u201calter the way in which NVIDIA\n\nsoftware performs computations and/or a description of the data input to NVIDIA software on\n\nwhich computations are run,\u201d which could be interpreted to encompass virtually any use of\n\nNVIDIA software and thus is unduly burdensome and disproportionate to the needs of the case;\n\n(3) it seeks information that is not within Google\u2019s possession, custody or control; (4) it seeks\n\ntestimony that is highly confidential, proprietary, that contains trade secrets, and/or is subject to a\n\nconfidentiality agreement or protective order.\n\n Accordingly, Google will not produce a witness to appear and testify on this topic at the\n\ntime and place requested by the Subpoena but will consider a properly tailored request after the\n\nparties have met and conferred to discuss this request.\n\nTOPIC NO. 4:\n\n Identification of Your software that uses NVIDIA GPUs to perform computations\n\nRESPONSE TO TOPIC NO. 4:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this topic on multiple grounds, including but not limited to the\n\n\n -12-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 14 of 18\n\n\n\n\nfollowing: (1) it is unduly burdensome and overbroad as it is not reasonably limited or discernible\n\nin scope\u2014especially for a non-party\u2014as to its request for testimony about any software that uses\n\nNVIDIA GPUs to perform computation without any meaningful limitation, which asks Google to\n\ntestify about every software system, application, or service across its entire computing\n\ninfrastructure that uses NVIDIA GPUs in any capacity; (2) it is vague and ambiguous, including\n\nbut not limited to the phrases \u201cYour\u201d(see Objection 6 above), \u201cuses NVIDIA GPUs to perform\n\ncomputations\u201d; (3) it seeks information that is not within Google\u2019s possession, custody or control;\n\n(4) it seeks testimony that is highly confidential, proprietary, that contains trade secrets, and/or is\n\nsubject to a confidentiality agreement or protective order.\n\n Accordingly, Google will not produce a witness to appear and testify on this topic at the\n\ntime and place requested by the Subpoena but will consider a properly tailored request after the\n\nparties have met and conferred to discuss this request.\n\nTOPIC NO. 5:\n\n Using Your software, the ways in which output data from a GPU computation(s), including\n\nintermediate results of GPU computations are stored, referenced by a pointer, transferred, copied,\n\nstreamed, written back, returned, accumulated, reused, or made available including asynchronously\n\nfrom NVIDIA GPU memory to CPU memory, host memory, system memory, storage, display,\n\nnetwork, or another memory location before, during, or in parallel with computations performed\n\nusing NVIDIA GPUs.\n\nRESPONSE TO TOPIC NO. 5:\n\n In addition to the above-listed objections, which are incorporated herein by reference,\n\nGoogle specifically objects to this topic on multiple grounds, including but not limited to the\n\nfollowing: (1) it is overbroad, technically complex, and unduly burdensome as it seeks testimony\n\n\n -13-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 15 of 18\n\n\n\n\nthat would require extraordinary witness preparation effort from a non-party, is not reasonably\n\nlimited or discernible in scope\u2014especially for a non-party\u2014as to its request for testimony about\n\nGPU memory management and data transfer operations across all of Google\u2019s GPU-utilizing\n\nsystems spanning the breadth of Google\u2019s computing infrastructure and product portfolio, which\n\nencompasses numerous distinct technical operations (storing, referencing by pointer, transferring,\n\ncopying, streaming, writing back, returning, accumulating, reusing, and asynchronous data\n\nmovement) for every system Google operates using NVIDIA GPUs; (2) it is vague and\n\nambiguous, including but not limited to the phrases \u201cYou\u201d (see Objection 6 above), \u201cthe ways in\n\nwhich output data from a GPU computation(s), including intermediate results of GPU\n\ncomputations are stored, referenced by a pointer, transferred, copied, streamed, written back,\n\nreturned, accumulated, reused, or made available including asynchronously from NVIDIA GPU\n\nmemory to CPU memory, host memory, system memory, storage, display, network, or another\n\nmemory location before, during, or in parallel with computations performed using NVIDIA\n\nGPUs\u201d; (3) it seeks information that is not within Google\u2019s possession, custody or control; (4) it\n\nseeks testimony that is highly confidential, proprietary, that contains trade secrets, and/or is\n\nsubject to a confidentiality agreement or protective order; (5) it seeks information that is not\n\nproportionate to the needs of the case and not relevant to any party\u2019s claims or defenses.\n\n Accordingly, Google will not produce a witness to appear and testify on this topic at the\n\ntime and place requested by the Subpoena but will consider a properly tailored request after the\n\nparties have met and conferred to discuss this request.\n\n\n\n\n -14-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 16 of 18\n\n\n\n\nDated: July 21, 2026 WILSON SONSINI GOODRICH & ROSATI\n Professional Corporation\n\n By: /s/ Jordan R. Jaffe\n Jordan R. Jaffe\n\n Attorney for Respondent\n Google LLC\n\n\n\n\n -15-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 17 of 18\n\n\n\n\n PROOF OF SERVICE\n\n I, Mercedes McKone, declare:\n\n I am employed in the County of San Francisco, in the State of California. I am over the age\n\nof 18 years and not a party to the within action. My business address is Wilson Sonsini Goodrich\n\n& Rosati, P.C., 12235 El Camino Real, San Diego, California, 92130.\n\n On this date, I served:\n\n RESPONSES AND OBJECTIONS OF NONPARTY GOOGLE LLC\n TO SUBPOENA TO TESTIFY AT A DEPOSITION IN A CIVIL ACTION\n\n \u2612 By forwarding the document(s) by electronic transmission on this date to the Internet\n\nemail address(es) listed below:\n\n Max L. Tribble, Esq. Tamar Lusztig, Esq.\n Brian D. Melton, Esq. Emily Portuguese, Esq.\n Rocco Magni, Esq. SUSMAN GODFREY L.L.P.\n Samuel Drezdzon, Esq. One Manhattan West, 50th Floor\n SUSMAN GODFREY L.L.P. New York, NY 10001\n 1000 Louisiana, Suite 5100 tlusztig@susmangodfrey.com\n Houston, TX 77002 eportuguese@susmangodfrey.com\n mtribble@susmangodfrey.com\n bmelton@susmangodfrey.com Mark D. Siegmund, Esq.\n rmagni@susmangodfrey.com CHERRY JOHNSON SIEGMUND JAMES PC\n sdrezdzon@susmangodfrey.com Bridgeview Center\n 7901 Fish Pond Road, 2nd Floor\n Tanner Laiche Waco, TX 76710\n SUSMAN GODFREY L.L.P. msiegmund@cjsjlaw.com\n 401 Union Street, Suite 3000\n Seattle, WA 98101 Attorneys for Plaintiff\n tlaiche@susmangodfrey.com NEURAL AI, LLC\n\n Max Ciccarelli\n CICCARELLI LAW FIRM LLC\n 100 N. 6th Street, Suite 502\n Waco, Texas 76701\n max@ciccarellilawfirm.com\n\n\n\n\n -1-\n\f Case 7:26-mc-00324-DC Document 1-11 Filed 08/18/26 Page 18 of 18\n\n\n\n\n I declare under penalty of perjury under the laws of the State of California that the foregoing\n\nis true and correct. Executed at San Diego, California on July 21, 2026.\n\n\n __________________________________\n Mercedes McKone\n\n\n\n\n -2-\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:25.650072-07:00","document_number":"1","attachment_number":11,"pacer_doc_id":"181037219906","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 10","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514525/","id":490514525,"tags":[],"absolute_url":"/docket/74667129/1/12/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.112628-07:00","date_modified":"2026-08-23T08:26:14.064814-07:00","sha1":"f6eef43be97b675079466c8abe1e74226460a75b","page_count":3,"file_size":127003,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.12.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.12.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-12 Filed 08/18/26 Page 1 of 3\n\n\n\n\n EXHIBIT\n\n 11\n\f Case 7:26-mc-00324-DC Document 1-12 Filed 08/18/26 Page 2 of 3\n\n\n Wednesday, August 5, 2026 at 4:58:41 PM Paci\ufb01c Daylight Time\n\nSubject: RE: Neural AI, LLC v. Nvidia Corporation, C.A. No. 7:24-cv-00221-ADA-DTG (W.D. Tex) - Subpoena to Google\n LLC\nDate: Monday, July 6, 2026 at 5:33:58 PM Paci\ufb01c Daylight Time\nFrom: JaWe, Jordan\nTo: Tanner Laiche, Emily Portuguese\nCC: Rocco Magni, Tamar Lusztig, Brian Melton, Max Tribble, Samuel Drezdzon, Richard Wojtczak, Rachel Hanna,\n Desai, Neil\n\n\nEXTERNAL Email\nThanks - Con\ufb01rming receipt of your email and the extension.\n\n\nJordan R. JaWe | Partner | Wilson Sonsini Goodrich & Rosati\nOne Market Plaza, Spear Tower, Suite 3300 | San Francisco, CA 94105\n415.498.0556 | jjaWe@wsgr.com | LinkedIn\n\n\nFrom: Tanner Laiche \nSent: Monday, July 6, 2026 4:54 PM\nTo: Ja\ufb00e, Jordan ; Emily Portuguese \nCc: Rocco Magni ; Tamar LuszMg ; Brian\nMelton ; Max Tribble ; Samuel\nDrezdzon ; Richard Wojtczak ;\nRachel Hanna \nSubject: Re: Neural AI, LLC v. Nvidia CorporaMon, C.A. No. 7:24-cv-00221-ADA-DTG (W.D. Tex) - Subpoena\nto Google LLC\n\nEXT - tlaiche@susmangodfrey.com\n\n\nCounsel,\n\nThanks for reaching out. Given the upcoming close of fact discovery, Neural AI is not\nable to agree to a two-week extension. That said, we can agree to a one-week\nextension for Google\u2019s written objections/responses to the subpoena(s), making the\nnew deadline July 21, 2026. We can likewise agree to move the deposition date by one\nweek.\n\nRegards,\n\nTanner Laiche\nSusman Godfrey LLP\n206.505.3816 | tlaiche@susmangodfrey.com\n401 Union Street | Suite 3000 | Seadle, WA 98101\nHOUSTON \u2022 LOS ANGELES \u2022 SEATTLE \u2022 NEW YORK\n\n\n\n\n 1 of 2\n\f Case 7:26-mc-00324-DC Document 1-12 Filed 08/18/26 Page 3 of 3\n\n\nFrom: JaWe, Jordan \nDate: Monday, July 6, 2026 at 3:27 /span>PM\nTo: Emily Portuguese \nSubject: Neural AI, LLC v. Nvidia Corporation, C.A. No. 7:24-cv-00221-ADA-DTG (W.D.\nTex) - Subpoena to Google LLC\n\nEXTERNAL Email\nDear Ms. Portuguese,\n\nMyself and my \ufb01rm have been recently retained by Google to respond to the subpoena\nissued to Google in this matter. We are still assessing the subpoena and conferring with\nour client.\n\nWill Neural AI agree to extend the time for any written objections/responses by two weeks?\nSpeci\ufb01cally, to July 28, 2026 for any objections/responses to the document subpoena.\nAnd can we similarly move the deposition subpoena return date a commensurate\namount? I.e., to August 4th, 2026.\n\nI\u2019m available to discuss if helpful.\n\nBest regards, Jordan\nJordan R. JaWe | Partner | Wilson Sonsini Goodrich & Rosati\nOne Market Plaza, Spear Tower, Suite 3300 | San Francisco, CA 94105\n415.498.0556 | jjaWe@wsgr.com | LinkedIn\n\n\n\n\nThis email and any attachments thereto may contain private, con\ufb01dential, and privileged\nmaterial for the sole use of the intended recipient. Any review, copying, or distribution of\nthis email (or any attachments thereto) by others is strictly prohibited. If you are not the\nintended recipient, please contact the sender immediately and permanently delete the\noriginal and any copies of this email and any attachments thereto.\n\n\nThis email and any attachments thereto may contain private, confidential, and privileged material\nfor the sole use of the intended recipient. Any review, copying, or distribution of this email (or\nany attachments thereto) by others is strictly prohibited. If you are not the intended recipient,\nplease contact the sender immediately and permanently delete the original and any copies of this\nemail and any attachments thereto.\n\n\n\n\n 2 of 2\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:21.533015-07:00","document_number":"1","attachment_number":12,"pacer_doc_id":"181037219907","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 11","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514526/","id":490514526,"tags":[],"absolute_url":"/docket/74667129/1/13/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.124842-07:00","date_modified":"2026-08-23T08:26:19.974469-07:00","sha1":"8629c6029fa49965000efecacdac235b2e589978","page_count":6,"file_size":146901,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.13.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.13.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-13 Filed 08/18/26 Page 1 of 6\n\n\n\n\n EXHIBIT\n\n 12\n\f Case 7:26-mc-00324-DC Document 1-13 Filed 08/18/26 Page 2 of 6\n\n\n Wednesday, August 5, 2026 at 3:28:34 PM Paci\ufb01c Daylight Time\n\nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\nDate: Tuesday, August 4, 2026 at 11:27:20 AM Paci\ufb01c Daylight Time\nFrom: Tanner Laiche\nTo: Rocco Magni, JaUe, Jordan, Desai, Neil\nCC: McKone, Mercedes, Max Tribble, Brian Melton, Samuel Drezdzon, max@ciccarellilaw\ufb01rm.com, Tamar Lusztig,\n Emily Portuguese, msiegmund, Grubbs, Deborah, Browder, Sissel, Margo, Ben, Wang, Jing (SF Associate), Pierce,\n Naomi, Arenas, G. Grace, Davidson, Nancy Fronda-\nAttachments: Neural AI, Third-Party Questions.docx, Neural AI, Draft Third-Party Declaration.docx\n\n\nCounsel,\n\nI am following up on this thread.\n\nDespite the parties\u2019 prior meet-and-confers, document discovery in the underlying action closes\non August 11. Unless the parties can promptly reach a resolution, that deadline leaves Neural AI\nno practical alternative but to move to compel by the end of this week or, at the latest, August 10,\nto preserve its rights.\n\nTo reduce burden and potentially avoid motion practice, I am attaching a set of questions intended\nto guide your investigation and help identify the responsive information, and also recirculating the\ndraft declaration we previously shared, and that Google may revise to ensure its accuracy.\n\nIf Google commits to provide an executed declaration, Neural AI is willing to consider accepting\nthe declaration in lieu of further document production and/or deposition testimony, subject to\nresolving any material gaps. Otherwise, the discovery deadline will force Neural AI to move to\ncompel by or before August 10 to preserve its rights. Even if a motion becomes necessary, we\nremain open to resolving the issues promptly and mooting or withdrawing the motion through\ncompliance.\n\nWe are available this week to further meet and confer as necessary.\n\nRegards,\n\nTanner Laiche\nSusman Godfrey LLP\n206.505.3816 | tlaiche@susmangodfrey.com\n401 Union Street | Suite 3000 | Seattle, WA 98101\nHOUSTON \u2022 LOS ANGELES \u2022 SEATTLE \u2022 NEW YORK\n\n\nFrom: Rocco Magni \nDate: Tuesday, July 28, 2026 at 4:29 PM\nTo: JaUe, Jordan ; Desai, Neil \nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; Tanner Laiche ;\nmax@ciccarellilaw\ufb01rm.com ; Tamar Lusztig\n\n 1 of 5\n\f Case 7:26-mc-00324-DC Document 1-13 Filed 08/18/26 Page 3 of 6\n\n\n; Emily Portuguese ;\nmsiegmund ; Grubbs, Deborah ; Browder,\nSissel ; Margo, Ben ; Wang, Jing (SF Associate)\n; Pierce, Naomi ; Arenas, G. Grace\n; Davidson, Nancy Fronda- \nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nJordan,\n\nPlease see attached template. Could we talk at 9:30 instead? I have another meeting at 10 now.\n\nThanks very much.\n\n--\nRocco F. Magni\nPartner | Susman Godfrey LLP\nO\ufb03ce: 713.653.7861\nCell: 512.514.3519\nFirm Bio\nThis e-mail may contain privileged and confidential information. If you received this message in error,\nplease notify the sender and delete it immediately.\nFrom: JaUe, Jordan \nDate: Monday, July 27, 2026 at 2:42 PM\nTo: Rocco Magni ; Desai, Neil \nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; Tanner Laiche ;\nmax@ciccarellilaw\ufb01rm.com ; Tamar Lusztig\n; Emily Portuguese ;\nmsiegmund ; Grubbs, Deborah ; Browder,\nSissel ; Margo, Ben ; Wang, Jing (SF Associate)\n; Pierce, Naomi ; Arenas, G. Grace\n; Davidson, Nancy Fronda- \nSubject: RE: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nEXTERNAL Email\nRocco et al.,\n\nThanks for speaking with us last Friday. As discussed, we are waiting on you all to send over a list\nof questions for our client and/or template declaration for us to review. We will plan to reconvene\nFriday at 10AM PT to discuss further.\n\nBest regards,\n\n\nJordan R. JaUe | Partner | Wilson Sonsini Goodrich & Rosati\nOne Market Plaza, Spear Tower, Suite 3300 | San Francisco, CA 94105\n\n\n 2 of 5\n\f Case 7:26-mc-00324-DC Document 1-13 Filed 08/18/26 Page 4 of 6\n\n\n415.498.0556 | jjaUe@wsgr.com | LinkedIn\n\n\nFrom: Rocco Magni \nSent: Wednesday, July 22, 2026 4:18 AM\nTo: Desai, Neil \nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; Tanner Laiche ;\nmax@ciccarellilawfirm.com; Tamar Lusztig ; Emily Portuguese\n; msiegmund ; Jaffe, Jordan\n; Grubbs, Deborah ; Browder, Sissel\n; Margo, Ben ; Pierce, Naomi ;\nArenas, G. Grace ; Davidson, Nancy Fronda- \nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nEXT - rmagni@susmangodfrey.com\n\n\nThat works. Thanks.\n--\nRocco F. Magni\nPartner | Susman Godfrey LLP\nOUice: 713.653.7861\nCell: 512.514.3519\n\nFirm Bio\n\nThis e-mail may contain privileged and con\ufb01dential information. If you received this message in\nerror, please notify the sender and delete it immediately.\n\n\n\n\n On Jul 21, 2026, at 11:54 PM, Desai, Neil wrote:\n\n\n EXTERNAL Email\n Rocco,\n\n How about Friday at 11 am PT?\n\n Neil Desai | Wilson Sonsini\n T 323.210.2912 | ndesai@wsgr.com\n\n From: Rocco Magni \n Sent: Tuesday, July 21, 2026 2:15 PM\n To: McKone, Mercedes \n Cc: Max Tribble ; Brian Melton\n ; Samuel Drezdzon ;\n Tanner Laiche ; max@ciccarellilawfirm.com; Tamar\n Lusztig ; Emily Portuguese\n\n 3 of 5\n\f Case 7:26-mc-00324-DC Document 1-13 Filed 08/18/26 Page 5 of 6\n\n\n; msiegmund ; Jaffe,\nJordan ; Desai, Neil ; Grubbs, Deborah\n; Browder, Sissel ; Margo, Ben\n; Pierce, Naomi ; Arenas, G. Grace\n; Davidson, Nancy Fronda- \nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nEXT - rmagni@susmangodfrey.com\n\n\nPlease provide times Friday to meet and confer. Thanks.\n--\nRocco F. Magni\nPartner | Susman Godfrey LLP\nOUice: 713.653.7861\nCell: 512.514.3519\n\nFirm Bio\n\nThis e-mail may contain privileged and con\ufb01dential information. If you received this\nmessage in error, please notify the sender and delete it immediately.\n\n\n\n\n On Jul 21, 2026, at 5:13 PM, McKone, Mercedes \n wrote:\n\n\n EXTERNAL Email\n Counsel:\n\n Please see the attached for electronic service.\n\n Thank you.\n\n \n\n Mercedes N. McKone | Executive Assistant | Wilson Sonsini Goodrich & Rosati\n 12235 El Camino Real | San Diego, CA 92130 | direct: 858.350.2217 | mmckone@wsgr.com\n \n\n\n\n\n \n\n\n\n\n This email and any attachments thereto may contain private, con\ufb01dential,\n and privileged material for the sole use of the intended recipient. Any\n review, copying, or distribution of this email (or any attachments thereto)\n\n 4 of 5\n\f Case 7:26-mc-00324-DC Document 1-13 Filed 08/18/26 Page 6 of 6\n\n\n by others is strictly prohibited. If you are not the intended recipient, please\n contact the sender immediately and permanently delete the original and\n any copies of this email and any attachments thereto.\n <2026-07-21 Responses and Objections to Deposition Subpoena.pdf>\n <2026-07-21 Responses and Objections to Document Subpoena.pdf>\n\n\n\n This email and any attachments thereto may contain private, con\ufb01dential, and\n privileged material for the sole use of the intended recipient. Any review, copying, or\n distribution of this email (or any attachments thereto) by others is strictly prohibited. If\n you are not the intended recipient, please contact the sender immediately and\n permanently delete the original and any copies of this email and any attachments\n thereto.\n\n\nThis email and any attachments thereto may contain private, confidential, and privileged material for the\nsole use of the intended recipient. Any review, copying, or distribution of this email (or any attachments\nthereto) by others is strictly prohibited. If you are not the intended recipient, please contact the sender\nimmediately and permanently delete the original and any copies of this email and any attachments\nthereto.\n\n\n\n\n 5 of 5\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:22.842203-07:00","document_number":"1","attachment_number":13,"pacer_doc_id":"181037219908","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 12","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514527/","id":490514527,"tags":[],"absolute_url":"/docket/74667129/1/14/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.135701-07:00","date_modified":"2026-08-23T08:26:19.061726-07:00","sha1":"c95c97390fee2e8804d72cf430c83b7840f6f7f1","page_count":3,"file_size":88888,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.14.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.14.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-14 Filed 08/18/26 Page 1 of 3\n\n\n\n\n EXHIBIT\n\n 13\n\f Case 7:26-mc-00324-DC Document 1-14 Filed 08/18/26 Page 2 of 3\n\n\n\n\nGeneral Deployment\n \u2022 Do you have architecture diagrams for your hardware and software systems that use\n NVIDIA GPUs?\n \u2022 Do you use PyTorch or TensorRT?\n \u2022 Which of the following, if any, top-layer applications do you use: Modulus, Maxine,\n cuQuantum, Merlin, Aerial, Monai, Triton, Nemo, VSS Blueprint, Riva, Metropolis,\n Holoscan, Clara Parabricks, Rapids, Isaac, Isaac Lab, Drive, DriveWorks, and\n Morpheus?\n \u2022 For each NVIDIA software product identified, in the ordinary course, do you download\n and use it locally, use it via a cloud-based solution offered by NVIDIA, or through a\n third-party cloud provider?\n \u2022 Do you make modifications to the source code for PyTorch, TensorRT, or other\n NVIDIA-provided software when its deployed on NVIDIA GPUs?\n \u2022 In the ordinary course, approximately how frequently do you run computations utilizing\n PyTorch or TensorRT on NVIDIA GPUs (e.g., many times per day, every day, every\n week, or every month)?\n \u2022 Are the relevant systems operated in the United States or used to support U.S.-directed\n operations?\n\nInput Data Path\n \u2022 In the ordinary course, do you use GPUDirect Storage (GDS) to load input data directly\n from storage into GPU memory, bypassing CPU main memory? Or do you use CPU\n main memory?\n \u2022 In the ordinary course, do you use GPUDirect RDMA or any direct NIC-to-GPU memory\n path for receiving live input data?\n \u2022 In the ordinary course, do you use unified memory (cudaMallocManaged), Unified\n Virtual Memory (UVM), or a coherent CPU/GPU memory architecture (e.g., DGX Spark\n UMA, Grace Hopper coherent memory) for the input data path?\n \u2022 In the ordinary course, do you use the PyTorch function torch.cuda.gds.GdsFile or any\n GDS-enabled data loader (e.g., DALI GDS, KvikIO) to load data?\n\nOutput Data Path and Memory Transfers\n \u2022 In the ordinary course, are outputs of GPU computations copied back to CPU/main\n memory? If so, what data is copied (e.g., transcripts, generated tokens, logits,\n embeddings)?\n \u2022 In the ordinary course, do GPU-to-CPU (D2H) or CPU-to-GPU (H2D) data transfers\n occur during or in parallel with GPU computations, or only after each computation\n completes?\n \u2022 In the ordinary course, how are your memory partitions configured for GPU\n computations? Are there separate memory regions for input data, output data, workspace,\n and intermediate results?\n \u2022 In the ordinary course, are output buffers from one GPU computation reused as input\n buffers for a subsequent computation?\n \u2022 Do you use torch.compile, TorchDynamo, Triton, TensorRT-LLM compilation, NVRTC,\n or PTX JIT to generate GPU programs at runtime, or do you use only precompiled\n kernels?\n\n\n\n 1\n\f Case 7:26-mc-00324-DC Document 1-14 Filed 08/18/26 Page 3 of 3\n\n\n\n\nTensorRT Usage\n \u2022 If you use TensorRT or TensorRT-LLM, how do you populate the input buffers and\n retrieve the outputs? Do you use CPU-side request processing and H2D/D2H copies?\n \u2022 Are TensorRT engines built by your organization, provided pre-built by NVIDIA, or\n obtained from another source?\n\n\n\n\n 2\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:23.683781-07:00","document_number":"1","attachment_number":14,"pacer_doc_id":"181037219909","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 13","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514528/","id":490514528,"tags":[],"absolute_url":"/docket/74667129/1/15/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.151398-07:00","date_modified":"2026-08-23T07:59:08.892923-07:00","sha1":"13482bc008b32d44a5799c4ab9b403fba58346f9","page_count":4,"file_size":84391,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.15.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.15.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-15 Filed 08/18/26 Page 1 of 4\n\n\n\n\n EXHIBIT\n\n 14\n\f Case 7:26-mc-00324-DC Document 1-15 Filed 08/18/26 Page 2 of 4\n\n\n\n\n UNITED STATES DISTRICT COURT\n WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\n\n NEURAL AI, LLC\n\n Plaintiff, Case No. 7:24-cv-00221-ADA-DTG\n v. JURY TRIAL DEMANDED\n NVIDIA CORPORATION\n\n Defendant.\n\n\n\n\n I, [DECLARANT NAME], hereby declare as follows:\n\n 1. I am [TITLE] of [COMPANY NAME]. I am over the age of eighteen and\n\ncompetent to make this declaration. I make this declaration based on my personal knowledge,\n\nincluding my general familiarity with [COMPANY NAME]\u2019s technical infrastructure, software\n\ndeployments, use of NVIDIA products, as well as the on the basis of a reasonably diligent\n\ninvestigation.\n\n 2. I understand that this declaration is submitted in connection with a subpoena served\n\non [INSERT DAT] on [COMPANY NAME] in the above-captioned action (the \u201cSubpoena\u201d).\n\n 3. In the ordinary course of business, [COMPANY NAME] uses NVIDIA GPUs (as\n\nthat term is defined in the Subpoena attached as Exhibit A) in its commercial operations.\n\nSpecifically, [COMPANY NAME] deploys GPUs of the [INSERT ARCHITECTURE]\n\narchitecture(s), including but not limited to [INSERT SPECIFIC GPU MODEL(S)] (collectively,\n\nthe \u201cDeployed NVIDIA GPUs\u201d).\n\n 4. In the ordinary course of business, [COMPANY NAME] uses the following\n\nNVIDIA offerings in connection with the Deployed NVIDIA GPUs: [Select among cuFFT,\n\f Case 7:26-mc-00324-DC Document 1-15 Filed 08/18/26 Page 3 of 4\n\n\n\n\ncuSparse, cuSolver, cuBlas, and cuDNN].\n\n 5. In the ordinary course of business, [COMPANY NAME] uses the following\n\nNVIDIA offerings in connection with the Deployed NVIDIA GPUs: [Select PyTorch and/or\n\nTensorRT].\n\n 6. In the ordinary course of business, [COMPANY NAME] uses the following\n\nNVIDIA offerings in connection with the Deployed NVIDIA GPUs: [Select among Modulus,\n\nMaxine, cuQuantum, Merlin, Ariel, Monai, Triton, Nemo, Riva, Metropolis, Holoscan, Clara\n\nParabricks, Rapids, Issac, Drive, and Morpheus].\n\n 7. In the ordinary course of business, [COMPANY NAME] uses the NVIDIA\n\nsoftware identified in Paragraphs 4-6 as provided by NVIDIA, without modification to the source\n\ncode.\n\n 8. To the best of [COMPANY NAME]\u2019s knowledge, when it uses the NVIDIA\n\nSoftware on the Deployed NVIDIA GPUs in the ordinary course of business, the hardware and\n\nNVIDIA software function together as designed and intended by NVIDIA.\n\n 9. In the ordinary course, [COMPANY NAME] uses one or more pretrained neural-\n\nnetwork models, model implementations, or model configurations distributed, made available, or\n\nrecommended by NVIDIA. In the ordinary course, [COMPANY NAME] deploys those models,\n\nimplementations, or configurations using PyTorch, TensorRT, or other NVIDIA software without\n\nmodifying their underlying network structure or low-level implementation code.\n\n 10. In the ordinary course of business, the Deployed NVIDIA GPUs are installed in\n\nsystems with separate CPU main memory and GPU memory, and the CPU and GPU in these\n\nsystems are connected via a bus.\n\n 11. In the ordinary course of business and for the operations described in this\n\f Case 7:26-mc-00324-DC Document 1-15 Filed 08/18/26 Page 4 of 4\n\n\n\n\ndeclaration, [COMPANY NAME] does not use Deployed NVIDIA GPUs with a unified\n\nCPU/GPU memory pool, GPUDirect Storage (\u201cGDS\u201d) to transfer input data directly from storage\n\nto GPU memory, NVIDIA Unified Virtual Memory (\u201cUVM\u201d), or CUDA managed memory to\n\nbypass the standard CPU-memory-to-GPU-memory data transfer path.\n\n 12. In [COMPANY NAME]\u2019s normal operations, when it uses the NVIDIA software\n\ndescribed in Paragraphs 4-6 on the Deployed NVIDIA GPUs, input data is received and processed\n\nby the CPU and stored in CPU main memory before being transferred to the GPU for computation.\n\nTo the best of my knowledge, this is the default and standard method by which data is loaded for\n\nprocessing on NVIDIA GPUs.\n\n 13. In the ordinary course of business and to the best of [COMPANY NAME]\u2019s\n\nknowledge, [COMPANY NAME] does not implement custom code or configurations that alter\n\nthe default data flow path provided by the NVIDIA Software with respect to how input data is\n\nreceived by the CPU, stored in main memory, and transferred to the GPU for computation.\n\n 14. To the best of [COMPANY NAME]\u2019s knowledge, the operations described in this\n\ndeclaration are performed in the United States using systems located in the United States or\n\nsystems that directly support [COMPANY NAME]\u2019s United States operations.\n\n 15. At least once per day, [COMPANY NAME] uses NVIDIA GPUs in conjunction\n\nwith at least one NVIDIA offering identified in each of Paragraphs 4-6.\n\n I declare under penalty of perjury under the laws of the United States of America that the\n\nforegoing is true and correct. Executed on [DATE], in [CITY, STATE].\n\n_______________________________________\n[DECLARANT NAME]\n[TITLE]\n[COMPANY NAME]\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:23.512176-07:00","document_number":"1","attachment_number":15,"pacer_doc_id":"181037219910","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 14","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514529/","id":490514529,"tags":[],"absolute_url":"/docket/74667129/1/16/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.163275-07:00","date_modified":"2026-08-23T01:58:51.389448-07:00","sha1":"6b8d194c484151ed02f5aaf5d47bdc2b52725c4a","page_count":4,"file_size":617519,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.16_1.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.16.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-16 Filed 08/18/26 Page 1 of 4\n\n\n\n\n EXHIBIT\n\n 15\n\f Case 7:26-mc-00324-DC Document 1-16 Filed 08/18/26 Page 2 of 4\n Company Blog Artificial Intelligence AI Infrastructure Physical AI Gaming & Creating Industries Subscribe US \uf2bd Sign In\n\n\n\n\nNVIDIA and Google Cloud Collaborate to Advance Agentic and Physical AI\nCompanies can build AI factories with NVIDIA Vera Rubin-powered A5X instances scaling up to nearly 1 million Rubin GPUs,\nGemini on Google Distributed Cloud, confidential NVIDIA Blackwell GPUs and agentic AI built on Gemini Enterprise Agent\nPlatform with NVIDIA Nemotron and NeMo.\nApril 22, 2026 by Ian Buck\n\n\n 6 mins 0 Share\n\n\n\n\nNVIDIA and Google Cloud have collaborated for more than a decade, co\u2011engineering a full\u2011stack AI platform that spans every technology\nlayer \u2014 from performance\u2011optimized libraries and frameworks to enterprise\u2011grade cloud services.\n\n\nThis foundation enables developers, startups and enterprises to push agentic and physical AI out of the lab and into production \u2014 from\nagents that manage complex workflows to robots and digital twins on the factory floor.\n\n\nAt Google Cloud Next this week in Las Vegas, the partnership reaches a new milestone, with advancements to expand Google Cloud AI\nHypercomputer for AI factories that will power the next frontier of agentic and physical AI.\n\n\nThese include the new NVIDIA Vera Rubin-powered A5X bare-metal instances; a preview of Google Gemini on Google Distributed Cloud NVIDIA GTC Berlin\nrunning on NVIDIA Blackwell and NVIDIA Blackwell Ultra GPUs; confidential VMs with NVIDIA Blackwell GPUs; and agentic AI on Gemini Registration Is Now Open\nEnterprise Agent Platform with NVIDIA Nemotron open models and the NVIDIA NeMo framework.\n October 20-22\n\nNext-Generation Infrastructure: From NVIDIA Blackwell to Vera Rubin Register Now\n\nAt Google Cloud Next, Google announced A5X powered by NVIDIA Vera Rubin NVL72 rack-scale systems, which \u2014 through extreme\ncodesign across chips, systems and software \u2014 deliver up to 10x lower inference cost per token and 10x higher token throughput per\nmegawatt than the prior generation.\n Recent News\nA5X will use NVIDIA ConnectX-9 SuperNICs, combined with next-generation Google Virgo networking, scaling to up to 80,000 NVIDIA\nRubin GPUs within a single site cluster and up to 960,000 NVIDIA Rubin GPUs in a multisite cluster, enabling customers to run their AI\n\nlargest AI workloads on NVIDIA\u2011optimized infrastructure.\n NVIDIA and Partners Build in America, for\n America\n\u201cAt Google Cloud, we believe the next decade of AI will be shaped by customers\u2019 ability to run their most demanding workloads on a truly\n August 5, 2026\nintegrated, AI\u2011optimized infrastructure stack,\u201d said Mark Lohmeyer, vice president and general manager of AI and computing\ninfrastructure at Google Cloud. \u201cBy combining Google Cloud\u2019s scalable infrastructure and managed AI services with NVIDIA\u2019s\nindustry\u2011leading platforms, systems and software, we\u2019re giving customers flexibility to train, tune and serve everything from frontier and AI Infrastructure\n\nopen models to agentic and physical AI workloads \u2014 while optimizing for performance, cost and sustainability.\u201d\n NVIDIA Joins NSF State and Regional AI\n Hubs Program to Expand AI Research and\nGoogle Cloud\u2019s broad NVIDIA Blackwell portfolio ranges from A4 VMs with NVIDIA HGX B200 systems to rack-scale A4X VMs with NVIDIA\n Education Across the US\nGB200 NVL72 and A4X Max NVIDIA GB300 NVL72 systems, all the way to fractional G4 VMs with NVIDIA RTX PRO 6000 Blackwell Server\n August 4, 2026\nEdition GPUs.\n\n\nCustomers can right-size their acceleration capabilities, whether using multiple interconnected NVL72 racks that scale out to tens of\nthousands of NVIDIA Blackwell GPUs, a single rack that can scale up to 72 Blackwell GPUs with fifth-generation NVIDIA NVLink and\nNVLink 5 Switch, or just one-eighth of a GPU.\n\n\nThis comprehensive platform helps teams optimize every workload, from mixture-of-experts reasoning, multimodal inference and data\nprocessing to complex simulations for the next frontier of physical AI and robotics.\n\f Case 7:26-mc-00324-DC Document 1-16 Filed 08/18/26 Page 3 of 4\nLeading frontier AI labs are already putting this infrastructure to work. Thinking Machines Lab is scaling its Tinker application Driving\n Company Blog Subscribe US\nprogramming interface (API) on A4X Max VMs with GB300 NVL72 systems to accelerate training, while OpenAI is running large\u2011scale\n NVIDIA Alpamayo 2 Super, the Frontier\ninference on NVIDIA GB300 (A4X Max VMs) and GB200 NVL72 systems (A4X VMs) on Google Cloud for some of its most demanding\n Open Model for Robotaxis and\ninference workloads, including for ChatGPT.\n Autonomous Vehicles, Now Available for\n Commercial Use\nSecure AI Wherever It Needs to Run: Sovereign and Confidential August 4, 2026\n\nGoogle Gemini models running on NVIDIA Blackwell and Blackwell Ultra GPUs are now in preview on Google Distributed Cloud, so\ncustomers can bring Google\u2019s frontier models wherever their most sensitive data resides. AI Infrastructure\n\n\n As AI Increases Demands on Memory,\nNVIDIA Confidential Computing with the NVIDIA Blackwell platform enables Gemini models to run in a protected environment where\n Storage Steps Up\nprompts and fine\u2011tuning data stay encrypted and can\u2019t be seen or altered by unauthorized parties, including the infrastructure\n August 4, 2026\noperators.\n\n\nIn the public cloud, the preview of Confidential G4 VMs with NVIDIA RTX PRO 6000 Blackwell GPUs brings these protections to View All Recent News\nmulti\u2011tenant environments \u2014 helping safeguard prompts, AI models and data so customers in regulated industries can access the power\nof AI without compromising on security or performance.\n\n\nThis is the first confidential computing offering of NVIDIA Blackwell GPUs in the cloud, giving Google Cloud customers a new foundation\nfor secure, high\u2011performance AI.\n\n\nOpen Models and APIs for Agentic AI\nThe NVIDIA platform on Google Cloud is optimized to run every kind of model \u2014 from Google\u2019s frontier Gemini and Gemma families to\nNVIDIA Nemotron open models and the broader open weight ecosystem \u2014 equipping developers to build agentic AI systems that reason,\nplan and act.\n\n\nNVIDIA Nemotron 3 Super is available on Gemini Enterprise Agent Platform, giving developers a direct path to discovering, customizing\nand deploying NVIDIA\u2011optimized reasoning and multimodal models for agentic workflows.\n\nGoogle Cloud and NVIDIA are also making it easier to train and customize open models at scale. Managed Training Clusters on Gemini\nEnterprise Agent Platform introduced a new managed reinforcement learning (RL) API built with NVIDIA NeMo RL for accelerating RL\ntraining at scale while automating cluster sizing, failure recovery and job execution, so teams can focus on agent behavior and model\nquality instead of infrastructure management.\n\nCybersecurity leader CrowdStrike uses NVIDIA NeMo open libraries such as NeMo Data Designer, NeMo Automodel and NeMo Megatron\nBridge to generate synthetic data and fine-tuning Nemotron and other open large language models for domain-specific cybersecurity.\nRunning on Managed Training Clusters on Gemini Enterprise Agent Platform with NVIDIA Blackwell GPUs, these capabilities accelerate\nthreat detection, investigation and response.\n\n\nBuilding the Future of Industrial and Physical AI\nBuilding industrial and physical AI at scale demands powerful hardware and a combination of open models, libraries and frameworks to\ndevelop these complex end-to-end workflows.\n\nNVIDIA AI infrastructure, open models and physical AI libraries available on Google Cloud, is mainstreaming industrial and physical AI\napplications, enabling customers to simulate, optimize and automate real-world workflows.\n\n\nSolutions from leading industrial software providers, including Cadence and Siemens Digital Industries Software, are now available on\nGoogle Cloud, accelerated on NVIDIA AI infrastructure. These applications are powering the next-generation design, engineering and\nmanufacturing of everything from chips to autonomous vehicles, robotics, aerospace platforms, heavy machinery and large-scale\nproduction systems.\n\n\nWith NVIDIA Omniverse libraries and the open source NVIDIA Isaac Sim robotics simulation framework available on Google Cloud\nMarketplace, developers can build physically accurate digital twins and develop custom robotics simulations pipelines to train, simulate\nand validate robots before real-world deployment.\n\n\nNVIDIA NIM microservices for models like NVIDIA Cosmos Reason 2 can be deployed to Google Vertex AI and Google Kubernetes Engine.\nThis enables robots and vision AI agents to see, reason and act in the physical world like humans, powering use cases such as automated\ndata curation and annotation, advanced robot planning and reasoning, and intelligent video analytics agents for real-time insights and\ndecision-making.\n\nTogether, these technologies help developers seamlessly move from computer-aided design to living industrial digital twins and AI\u2011driven\nrobots, accelerating processes from design sign\u2011off to factory optimization on the NVIDIA platform running on Google Cloud.\n\n\nProven Impact: From Startups to Global Enterprises\nGlobal enterprises, AI labs and high\u2011growth startups are using NVIDIA and Google Cloud\u2019s co-engineered platform to move from\nprototyping to production faster, including Snap, Schr\u00f6 dinger and Salesforce. Snap is cutting the cost of large\u2011scale A/B testing by\nshifting data pipelines to GPU\u2011accelerated Spark on Google Cloud. Schr\u00f6 dinger is shrinking weekslong drug discovery simulations into\njust hours with NVIDIA accelerated computing on Google Cloud.\n\n\nStartups are orchestrating the next wave of AI innovation \u2014 building new agents and AI\u2011native applications using NVIDIA accelerated\ncomputing on Google Cloud.\n\nAs part of a broader ecosystem highlighted through NVIDIA Inception and Google for Startups, CodeRabbit and Factory are using NVIDIA\nNemotron\u2011based models on Google Cloud to power code review and autonomous software development agents, while Aible, Mantis AI,\nPhotoroom and Baseten are building enterprise data, video intelligence, generative imagery and managed inference solutions on the\nfull\u2011stack NVIDIA platform on Google Cloud.\n\n\nMore than 90,000 developers have become a part of the joint NVIDIA and Google Cloud developer community in just over a year, tapping\nthis platform to build and scale new AI applications.\n\nIn addition, NVIDIA has been honored at Next as Google Cloud Partner of the Year in two categories \u2014 AI Global Technology Partner and\nInfra Modernization Compute \u2014 in recognition of deep technical expertise and go-to-market alignment.\n\f Case 7:26-mc-00324-DC Document 1-16 Filed 08/18/26 Page 4 of 4\nTogether, NVIDIA and Google Cloud are giving customers a cloud\u2011scale platform to turn experimental agents and simulations into\n Company Blog Subscribe US\nproduction systems that review code, secure fleets, enable new AI applications and optimize factories in the real world.\n\nLearn more about the companies\u2019 collaboration by attending NVIDIA sessions, demos and workshops at Google Cloud Next.\n\n\nCategories: AI Infrastructure Cloud\n\n\n\nTags: Agentic AI Artificial Intelligence Cloud Services Cosmos Inception Isaac Nemotron NVIDIA Blackwell NVIDIA NeMo NVIDIA Rubin NVLink Omniverse\n\n\n Open Source Physical AI\n\n\n\n\n Comments for this thread are now closed \u00d7\n\n\n0 Comments \ue603\n 1 Login\n\n\n\n \uf109 7 Share Best Newest Oldest\n\n\n\n\n This discussion has been closed.\n\n\n\n\n Subscribe Privacy Do Not Sell My Data\n\n\n\n\nRelated News\n\n\n\n\n AI Infrastructure AI Infrastructure AI Infrastructure Networking\n\n\nNVIDIA Joins NSF State and NVIDIA AI Supercomputer NVIDIA Vera Rubin Driving Built for Vera Rubin, NVIDIA\nRegional AI Hubs Program to Comes Online at Naval Performance Per Watt, Lowest Spectrum-6 Arrives in\nExpand AI Research and Postgraduate School Token Cost for Partners Gigascale AI Factories\nEducation Across the US Jul 22, 2026 Worldwide Jul 21, 2026\n\nAug 4, 2026 Jul 21, 2026\n\n\n\n\n Follow Us \uf39e \uf16d \uf0e1 \ue61b \uf167\n\n\n United States\n\nPrivacy Policy Your Privacy Choices Terms of Service Accessibility Corporate Policies Product Security Contact\nCopyright \u00a9 2026 NVIDIA Corporation\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:32.929614-07:00","document_number":"1","attachment_number":16,"pacer_doc_id":"181037219911","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 15","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514530/","id":490514530,"tags":[],"absolute_url":"/docket/74667129/1/17/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.175783-07:00","date_modified":"2026-08-23T08:26:36.904195-07:00","sha1":"7345db24f258184d30db59572b45ed1d52b51d6e","page_count":5,"file_size":11334398,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.17_1.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.17.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-17 Filed 08/18/26 Page 1 of 5\n\n\n\n\n EXHIBIT\n\n 16\n\fCase 7:26-mc-00324-DC Document 1-17 Filed 08/18/26 Page 2 of 5\n Join our developer community\n\n\n\n\n Accelerate innovation on Google\n Cloud and NVIDIA\n NVIDIA and Google Cloud provide accelerator-optimized solutions that support\n demanding workloads, including generative AI, high-performance computing, data\n analytics, graphics, and gaming workloads.\n\n\n Contact us 0:45\n\n Engineering what's next\n\n\n\n\n Google Distributed Cloud runs AI\n models on-premises\n Learn how Google Cloud and NVIDIA collaborate to provide\n Gemini and generative AI to the edge and regulated\n environments with Google Distributed Cloud.\n\n Watch video\n\n\n 0:54\n\n\n\n\n NVIDIA-accelerated computing on Google Cloud\n\n NVIDIA GTC 2026 Highlights NVIDIA GPUs on Google Cloud Product integrations Documentation\n\n\n\n\n Recapping on NVIDIA GTC 2026 San Jose. See the highlights: View Google Cloud-led sessions at NVIDIA\n GTC\n View industry-leading announcements\n Explore Sponsored sessions on demand: Blueprint for AI scale: How industry Blueprint for AI scale: How\n Aarchitects success with NVIDIA GPUs on Google Cloud and Scale Foundation Industry architects success With\n Models with Google Cloud AI Hypercomputer NVIDIA GPUs on Google Cloud\n Watch our latest AI Podcast\ufeff Watch here\n\n View our session catalog\n Scale foundation models on\n Google Cloud AI Hypercomputer\n \u201cWe are moving from training AI to producing intelligence. These data Watch now\n\n centers are no longer just storing information. They are factories\n generating tokens, generating intelligence... Our expanded collaboration\n with Google Cloud will help developers accelerate their work with\n infrastructure that supercharges energy efficiency and reduces costs.\u201d\n Jensen Huang, GTC 2026 keynote\n\fCase 7:26-mc-00324-DC Document 1-17 Filed 08/18/26 Page 3 of 5\n\n Watch the latest AI podcast: Tiffany\n Janzen sits down with Google Cloud\n Chelsie Czop to discuss the partnership\n between NVIDIA and Google Cloud and\n the future of AI Infrastructure\n Recorded at NVIDIA GTC Insights studio\n\n\n Watch now\n\n\n\n\n Google Cloud and NVIDIA partnership\n\n\n\n\n Google Cloud and NVIDIA technical Google Cloud and NVIDIA Inception Public sector\n community startups community At Google Public Sector Summit, Ian Buck, VP\n Google Cloud and NVIDIA have partner to Google Cloud and NVIDIA Inception are of Hyperscale and high-performance\n provide this community for developers, data connecting with the startup and AI ecosystem computing at NVIDIA, sits down with Thomas\n scientists, AI/ML engineers, and technical and educating startups on NVIDIA Kurian, CEO-Google Cloud to discuss the two\n practitioners who use NVIDIA and Google technologies on Google Cloud, through-joint companies long-standing partnership and\n Cloud technologies for their development. events like GTC and Next, webinars, full-stack co-engineering to deploy AI at scale\n Earn your developer badges. workshops, customer stories, and joint offers. that advances AI leadership in the US public\n View our featured customer, Augment Code, sector.\n to learn how they accelerate AI coding with 00:25:22\n\n Google Cloud and NVIDIA.\n 00:04:08\n\n\n\n\n Watch how success story featuring Augment Watch Thomas Kurian in the Public Sector\n Join the community Code Summit keynote\n\n\n\n\n NVIDIA on Google Cloud marketplace\n\n\n\n\n NVIDIA Omniverse NVIDIA DGX Cloud NVIDIA AI Enterprise\n A platform of APIs, SDKs, and services that let NVIDIA DGX Cloud accelerates AI workloads in A cloud-native platform that streamlines\n developers integrate OpenUSD, NVIDIA RTX\u2122 the cloud, provides high-performance development and deployment of production-\n rendering technologies into physical AI training, scalable inference, and global GPU grade AI solutions-including generative AI,\n applications. Use virtual machines (VMs) on access for developers and platform teams. computer vision, speech AI.\n Google Cloud to streamline your application\n development.\n\fCase 7:26-mc-00324-DC Document 1-17 Filed 08/18/26 Page 4 of 5\n\n\n\n Customer stories\n\n\n\n\n 2:37\n\n\n\n Learn how SandboxAQ accelerates scientific discovery with AI\n\n\n\n\n 2:52\n\n\n\n Learn how PUMA built an AI jersey designer with Google Cloud and NVIDIA\n\n\n\n\n Augment Code\n Augment Code speeds up AI coding on Google Cloud and\n NVIDIA\n\n Watch video\n\n\n\n 4:08\n\n\n\n\n Galileo\n Galileo: De-risk LLMs and build reliable AI apps at scale\n with Gemini, NVIDIA, and Google Cloud\n\n Read customer story\n\fCase 7:26-mc-00324-DC Document 1-17 Filed 08/18/26 Page 5 of 5\n Baseten\n How Baseten achieves 225% better cost-performance for\n AI inference with NVIDIA and Google Cloud\n\n Read customer story\n\n\n\n\n LiveX AI\n LiveX AI reduces support costs by 85% using GKE and\n NVIDIA AI-powered agents\n\n Read customer story\n\n\n\n\n \u201c\n Compared with another inference platform, running on GKE\n with NVIDIA NIM and GPUs delivered 6.1x acceleration in\n average answer/response generation speed for the Amazfit AI\n agent.\n Jia Li Co-Founder, Chief AI Officer, LiveX AI\n\n\n Read more\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:35.308037-07:00","document_number":"1","attachment_number":17,"pacer_doc_id":"181037219912","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 16","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514531/","id":490514531,"tags":[],"absolute_url":"/docket/74667129/1/18/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.187809-07:00","date_modified":"2026-08-23T02:41:36.026925-07:00","sha1":"7e8b6eaa2590b72ab3dc5ff37f48885883863188","page_count":2,"file_size":1120667,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.18.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.18.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-18 Filed 08/18/26 Page 1 of 2\n\n\n\n\n EXHIBIT\n\n 17\n\f Case 7:26-mc-00324-DC Document 1-18 Filed 08/18/26 Page 2 of 2\n Careers help_outline feedback\n\n home\n Home\n\n\n\n work_outline\n Jobs\n\n\n noogler_hat\nStudents\n\n\n google\nHow we\n work\n\n\n handyman\n Austin\nHow we\n hire The Google Austin site is located in the heart of the state\u2019s capital and serves as a hub for Corporate\n\n\n person_outline\n Social Responsibility efforts. Austin Googlers can experience offices inspired by the Austin\n landscape, a speakeasy meet up space, art by local artists, rooftop cafe views, a dog park, and\n\n Your 167 jobs available more. Outside the office, Googlers are in the \u201cLive Music Capital of the World,\u201d the home of SXSW\n career and ACL Festivals, and one of the highest ranking tech cities in the US. The Austin site has a diverse\n product area makeup with roles in Corporate Engineering, Google Cloud, People Operations, Fiber,\n Finance, Legal, and more.\n View all jobs\n\n\n\n\n Business Strategy Engineering & Technology Legal\n See 15 jobs See 104 jobs See 7 jobs\n\n\n\n\n Marketing & Communications People Sales, Service & Support\n See 5 jobs See 5 jobs See 37 jobs\n\n\n\n\n Our plans to invest $9.5 billion in the My Path to Google \u2014 Callen Therrien, Interview Tips \u2014 Google Careers\n U.S. in 2022 Cloud Technical Resident\n Read more Read more Read more\n\n\n\n\n Follow Life at Google on\n\n\n\n\n More about us Related Information Equal Opportunity\n\n About us open_in_new Investor relations open_in_new Google is proud to be an equal opportunity and affirmative action employer. We are\n committed to building a workforce that is representative of the users we serve,\n Contact us open_in_new Blog open_in_new creating a culture of belonging, and providing an equal employment opportunity\n regardless of race, creed, color, religion, gender, sexual orientation, gender\n identity/expression, national origin, disability, age, genetic information, veteran\n Press open_in_new\n status, marital status, pregnancy or related condition (including breastfeeding),\n expecting or parents-to-be, criminal histories consistent with legal requirements, or\n any other basis protected by law. See also Google's EEO Policy, Know your rights:\n workplace discrimination is illegal, Belonging at Google, and How we hire.\n\n\n\n\n Privacy open_in_new Applicant & Candidate Privacy open_in_new Terms open_in_new help Help open_in_new language English\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:29.512628-07:00","document_number":"1","attachment_number":18,"pacer_doc_id":"181037219913","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 17","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514532/","id":490514532,"tags":[],"absolute_url":"/docket/74667129/1/19/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.199128-07:00","date_modified":"2026-08-23T08:26:20.518612-07:00","sha1":"5010917274ffbd5ebb53af551eef569206888657","page_count":3,"file_size":9919922,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.19.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.19.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-19 Filed 08/18/26 Page 1 of 3\n\n\n\n\n EXHIBIT\n\n 18\n\f Case 7:26-mc-00324-DC Document 1-19 Filed 08/18/26 Page 2 of 3\n\n\n Home Company News Inside Google Company Announcements\n\n\n\n\n Coming soon to the Lone Star\n State: more office space and a\n data center\n Jun 14, 2019\n 2 min read\n\n\n\n Andrew Silvestri\n Share\n Public Policy and Community Development Lead, Americas\n\n\n\n\nWe're expanding in Texas. Austin has been\nhome to Google for over a decade and\ntoday, we\u2019re extending our commitment to\nthe state with a new data center in\nMidlothian, and the lease of two new\nbuildings for our Austin workforce. These\nnew commitments are part of our larger $13\nbillion investment in offices and data\ncenters across the United States, which\nwe announced earlier this year.\n\n\n\n\nBreaking ground at our new Midlothian Data\nCenter\n\n\n\nWe\u2019re investing $600 million to develop the\nMidlothian site, which will create a number\nof full-time jobs, as well as hundreds of\nconstruction jobs to build the new data\ncenter. As part of this investment, we\u2019re\nalso making a $100,000 grant to the\nMidlothian Independent School District to\nsupport the continued growth and\ndevelopment of the region\u2019s STEM\nprograms in schools.\n\f Case 7:26-mc-00324-DC Document 1-19 Filed 08/18/26 Page 3 of 3\n\n In Austin, we already have more than 1,100\n employees working across Android, G\n Suite, Google Play, Cloud, staffing and\n recruiting, people operations, finance and\n marketing. As we continue to grow, we\u2019ve\n leased additional office space at Block 185\n and Saltillo\u2014located in downtown Austin\n and east Austin, respectively\u2014to\n accommodate our short and long-term\n growth.\n\n\n\n\n Our current downtown Austin office on W 2nd\n Street. We will maintain our presence there while\u2026\n\n\n\n The Lone Star state has become a hub for\n tech innovation and we\u2019ve been fortunate\n to be a part of its growth from the very\n beginning. It\u2019s the amazing talent and spirit\n of work and play that brought us to Texas 12\n years ago and it\u2019s what keeps us here today.\n We look forward to meeting our new\n neighbors in the Midlothian-Dallas Metro\n area and we\u2019re excited to be a part of these\n communities for many years to come.\n\n\n\n POSTED IN:\n Company announcements Global Network\n\n\n\n\n Related stories\n Global Network\n\n We\u2019re strengthening our\n presence in Alabama through\n new investments and\u2026\n Google has announced a $1.5 billion\n investment for 2026 and 2027 to expand its\n data center campus in Jackson County,\n Alabama. Operating since 2019 on a\n repurposed former\u2026\n\n\n\n\nCompany announcements Creating opportunity Global Network Global Network G\n\nWelcome to Sail Tower, our We\u2019re announcing the Alliance Our largest solar and battery Our new community G\nnewest Austin office for America\u2019s Skilled Trades. storage project ever investments in Virginia support A\n local jobs and expand energy\u2026\nBy Scott Foster By Will Conkling & Christopher Scott B\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:30.935531-07:00","document_number":"1","attachment_number":19,"pacer_doc_id":"181037219914","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 18","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514533/","id":490514533,"tags":[],"absolute_url":"/docket/74667129/1/20/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.209764-07:00","date_modified":"2026-08-23T08:29:14.978792-07:00","sha1":"71123c477ccc0a68400f58312cadcde44d59f7a6","page_count":2,"file_size":439771,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.20.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.20.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-20 Filed 08/18/26 Page 1 of 2\n\n\n\n\n EXHIBIT\n\n 19\n\f Case 7:26-mc-00324-DC Document 1-20 Filed 08/18/26 Page 2 of 2\n\n\n\n\n Our locations\n Each one of our offices is designed to inspire big ideas and build community. Explore our locations around the\n world.\n\n\n\n\n North America Latin America Europe Asia Pacific Africa & Middle East\n\n\n\n\n North America\n Ann Arbor\n\n Atlanta\n\n Austin (2)\n\n Google Austin - 500\n W 2nd St\n\n Google Austin - Sail\n Tower\n\n\n Boulder (2)\n\n Cambridge\n\n Chicago (2)\n\n Dallas\n\n Detroit\n\n Durham\n\n H t\n Map data \u00a92026 Google, INEGI\n\n\n\n\nResources Outreach and initiatives Research and technology More about us\n\nBlog Accessibility Google AI Around the globe\n\nBrand Resource Center Crisis Response Google Cloud Human rights\n\nCareers Google.org Google DeepMind Safety Center\n\nContact us Google for Health Google for Developers Supplier responsibility\n\nHelp Center Grow with Google Google Labs Transparency Center\n\nInvestor Relations Learning Google Research Transparency Report\n\nLocations Public Policy\n\nPress resources Sustainability\n\n\n\n\n Privacy Terms Help English\n\f","ocr_status":1,"date_upload":"2026-08-20T10:55:29.990960-07:00","document_number":"1","attachment_number":20,"pacer_doc_id":"181037219915","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 19","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514534/","id":490514534,"tags":[],"absolute_url":"/docket/74667129/1/21/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.221533-07:00","date_modified":"2026-08-22T23:43:38.604136-07:00","sha1":"acdeaaf14e1998846f99334b97d29f68eb7bf802","page_count":13,"file_size":281679,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.21.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.21.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 1 of 13\n\n\n\n\n EXHIBIT\n\n 20\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 2 of 13\n\n\n Tuesday, August 18, 2026 at 10:02:42 AM Paci\ufb01c Daylight Time\n\nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\nDate: Tuesday, August 18, 2026 at 10:02:35 AM Paci\ufb01c Daylight Time\nFrom: Tanner Laiche\nTo: JaTe, Jordan, Rocco Magni, Desai, Neil\nCC: McKone, Mercedes, Max Tribble, Brian Melton, Samuel Drezdzon, max@ciccarellilaw\ufb01rm.com, Tamar Lusztig,\n Emily Portuguese, msiegmund, Grubbs, Deborah, Browder, Sissel, Margo, Ben, Wang, Jing (SF Associate), Pierce,\n Naomi, Arenas, G. Grace, Davidson, Nancy Fronda-\nAttachments: Neural AI, Draft Third-Party Declaration (revised).docx\n\n\nCounsel,\n\nFollowing up on our discussion yesterday, please see the attached revised declaration addressing\nParagraph 11, which we believe accurately re\ufb02ects Google\u2019s operations.\n\nTo reduce the burden on Google, NAI is willing to consider Google\u2019s discovery obligations satis\ufb01ed\nif Google either (1) executes a revised declaration addressing the issues identi\ufb01ed in the attached\ndraft without material gaps, or (2) produces documents suTicient to establish each of those\nissues. We are, of course, happy to discuss any further revisions Google believes are necessary to\nensure the declaration is accurate while still addressing the material issues underlying NAI\u2019s\nrequests.\n\nRegards,\n\nTanner Laiche\nSusman Godfrey LLP\n206.505.3816 | tlaiche@susmangodfrey.com\n401 Union Street | Suite 3000 | Seattle, WA 98101\nHOUSTON \u2022 LOS ANGELES \u2022 SEATTLE \u2022 NEW YORK\nThis e-mail contains privileged and con\ufb01dential information, which may be subject to the attorney-client privilege\nand/or attorney work product protection. If you received this message in error, please notify the sender and delete it\nimmediately.\n\n\nFrom: Tanner Laiche \nDate: Tuesday, August 18, 2026 at 5:07 AM\nTo: JaTe, Jordan ; Rocco Magni ; Desai, Neil\n\nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; max@ciccarellilaw\ufb01rm.com ;\nTamar Lusztig ; Emily Portuguese\n; msiegmund ; Grubbs,\nDeborah ; Browder, Sissel ; Margo, Ben\n; Wang, Jing (SF Associate) ; Pierce, Naomi\n; Arenas, G. Grace ; Davidson, Nancy Fronda-\n\nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\n\n 1 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 3 of 13\n\n\nJordan,\n\nThanks for the call. After discussing internally, we are comfortable with language stating that, in\nconjunction with Paragraph 11 regarding various forms of shared memory, Google uses a CPU to\ninitiate model inference and/or uses a CPU to pass input data to and interact with the ML model\nrunning on the GPU.\n\nGiven today\u2019s deadline, we intend to \ufb01le a motion solely to preserve our rights and avoid any\npotential waiver of discovery from Google. We will continue working with Google toward a\nresolution and will promptly withdraw the motion if the parties are able to resolve the subpoena\ndiscovery.\n\nRegards,\n\nTanner Laiche\nSusman Godfrey LLP\n206.505.3816 | tlaiche@susmangodfrey.com\n401 Union Street | Suite 3000 | Seattle, WA 98101\nHOUSTON \u2022 LOS ANGELES \u2022 SEATTLE \u2022 NEW YORK\nThis e-mail contains privileged and con\ufb01dential information, which may be subject to the attorney-client privilege\nand/or attorney work product protection. If you received this message in error, please notify the sender and delete it\nimmediately.\n\n\nFrom: JaTe, Jordan \nDate: Monday, August 17, 2026 at 10:50 AM\nTo: Tanner Laiche ; Rocco Magni\n; Desai, Neil \nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; max@ciccarellilaw\ufb01rm.com ;\nTamar Lusztig ; Emily Portuguese\n; msiegmund ; Grubbs,\nDeborah ; Browder, Sissel ; Margo, Ben\n; Wang, Jing (SF Associate) ; Pierce, Naomi\n; Arenas, G. Grace ; Davidson, Nancy Fronda-\n\nSubject: RE: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nEXTERNAL Email\nTanner,\n\nI can do 4:30 pm PT. Please send an invite if that works for you.\n\nBest regards,\n\n\nJordan R. JaTe | Partner | Wilson Sonsini Goodrich & Rosati\nOne Market Plaza, Spear Tower, Suite 3300 | San Francisco, CA 94105\n415.498.0556 | jjaTe@wsgr.com | LinkedIn\n\n 2 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 4 of 13\n\n\n\nFrom: Tanner Laiche \nSent: Sunday, August 16, 2026 3:06 PM\nTo: Jaffe, Jordan ; Rocco Magni ; Desai, Neil\n\nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; max@ciccarellilawfirm.com; Tamar Lusztig\n; Emily Portuguese ;\nmsiegmund ; Grubbs, Deborah ; Browder, Sissel\n; Margo, Ben ; Wang, Jing (SF Associate)\n; Pierce, Naomi ; Arenas, G. Grace\n; Davidson, Nancy Fronda- \nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nEXT - tlaiche@susmangodfrey.com\n\n\nCounsel,\n\nApologies for the delayed response\u2014I was in depositions last week. I am available tomorrow after\n2:00 pm PT. Please let me know if a time in that window works for you.\n\nThanks,\n\nTanner Laiche\nSusman Godfrey LLP\n206.505.3816 | tlaiche@susmangodfrey.com\n401 Union Street | Suite 3000 | Seattle, WA 98101\nHOUSTON \u2022 LOS ANGELES \u2022 SEATTLE \u2022 NEW YORK\nThis e-mail contains privileged and con\ufb01dential information, which may be subject to the attorney-client privilege\nand/or attorney work product protection. If you received this message in error, please notify the sender and delete it\nimmediately.\n\n\nFrom: JaTe, Jordan \nDate: Thursday, August 13, 2026 at 3:39 PM\nTo: Tanner Laiche ; Rocco Magni\n; Desai, Neil \nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; max@ciccarellilaw\ufb01rm.com ;\nTamar Lusztig ; Emily Portuguese\n; msiegmund ; Grubbs,\nDeborah ; Browder, Sissel ; Margo, Ben\n; Wang, Jing (SF Associate) ; Pierce, Naomi\n; Arenas, G. Grace ; Davidson, Nancy Fronda-\n\nSubject: RE: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nEXTERNAL Email\n\n 3 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 5 of 13\n\n\nTanner,\n\nWe have an update on our end. Please let us know if you\u2019re available to meet and confer\ntomorrow. We can be between 9am and noon PT. Alternatively, if easier, I\u2019m available this\nafternoon between now and 5:30 pm pt.\n\nBest regards,\n\n\nJordan R. JaTe | Partner | Wilson Sonsini Goodrich & Rosati\nOne Market Plaza, Spear Tower, Suite 3300 | San Francisco, CA 94105\n415.498.0556 | jjaTe@wsgr.com | LinkedIn\n\n\nFrom: Tanner Laiche \nSent: Tuesday, August 11, 2026 9:48 AM\nTo: Jaffe, Jordan ; Rocco Magni ; Desai, Neil\n\nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; max@ciccarellilawfirm.com; Tamar Lusztig\n; Emily Portuguese ;\nmsiegmund ; Grubbs, Deborah ; Browder, Sissel\n; Margo, Ben ; Wang, Jing (SF Associate)\n; Pierce, Naomi ; Arenas, G. Grace\n; Davidson, Nancy Fronda- \nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nEXT - tlaiche@susmangodfrey.com\n\n\nCounsel,\n\nThank you for your email.\n\nAs an update, NVIDIA has agreed to extend Neural AI\u2019s deadline to \ufb01le third-party discovery\nmotions through August 18. We would like to use that additional time to try to resolve the\noutstanding issues.\n\nWe appreciate Google's continued investigation. As previously discussed, we sent you a proposed\ndeclaration that we believe could provide a basis to resolve the subpoenas. Please send us any\nproposed edits to the declaration as soon as possible so that we can evaluate whether the\ndeclaration, as revised, would address the information sought by the subpoenas and avoid the\nneed for additional discovery. To that end, we would appreciate the opportunity to review any\nproposed revisions before the declaration is \ufb01nalized or executed.\n\nGiven the timing, we would appreciate receiving your edits promptly. If we are unable to reach a\nresolution before the August 18 deadline, Neural AI will need to \ufb01le a motion to preserve its rights\nand avoid any argument that it waived the issue. That would not prevent the parties from\ncontinuing to work toward a resolution. If we subsequently reach an agreement that resolves the\n\n\n 4 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 6 of 13\n\n\noutstanding discovery, Neural AI would promptly withdraw the motion.\n\nRegards,\n\nTanner Laiche\nSusman Godfrey LLP\n206.505.3816 | tlaiche@susmangodfrey.com\n401 Union Street | Suite 3000 | Seattle, WA 98101\nHOUSTON \u2022 LOS ANGELES \u2022 SEATTLE \u2022 NEW YORK\n\n\nFrom: JaTe, Jordan \nDate: Friday, August 7, 2026 at 9:22 AM\nTo: Tanner Laiche ; Rocco Magni\n; Desai, Neil \nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; max@ciccarellilaw\ufb01rm.com ;\nTamar Lusztig ; Emily Portuguese\n; msiegmund ; Grubbs,\nDeborah ; Browder, Sissel ; Margo, Ben\n; Wang, Jing (SF Associate) ; Pierce, Naomi\n; Arenas, G. Grace ; Davidson, Nancy Fronda-\n\nSubject: RE: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\nEXTERNAL Email\nTanner,\nNeural AI\u2019s counsel suggested during our meet and confer that the requests to Google were\nreasonable and directed to relevant evidence in view of Judge Gilland\u2019s comments regarding the\nDell subpoena. Now Neural AI is saying that Google is \u201cdiTerently situated\u201d than Dell. It is unclear\nwhy Neural AI brought up Judge Gilliland\u2019s comments if that is the case.\nThank you for con\ufb01rming your agreement that a declaration would suTice to resolve Google\u2019s\nobligations under the subpoenas. We understand that you want to have some sense of what is in\nthe declaration beforehand. We can work with that in mind.\nFinally, on timing, Google\u2019s ability to investigate these topics has been hampered by Neural AI\u2019s\ncontinued failure to narrow the scope of any of its overbroad requests. In addition, Neural AI only\nprovided its \u201cquestions\u201d to Google on August 4. While Google continues to investigate these\nmatters diligently, we may not have an update by 4:00 pm CT on Monday. We will provide an\nupdate as soon as we can next week.\nBest regards,\n\n\n\nJordan R. JaTe | Partner | Wilson Sonsini Goodrich & Rosati\nOne Market Plaza, Spear Tower, Suite 3300 | San Francisco, CA 94105\n415.498.0556 | jjaTe@wsgr.com | LinkedIn\n\n\nFrom: Tanner Laiche \nSent: Thursday, August 6, 2026 1:09 PM\n\n\n 5 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 7 of 13\n\n\nTo: Jaffe, Jordan ; Rocco Magni ; Desai, Neil\n\nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; max@ciccarellilawfirm.com; Tamar Lusztig\n; Emily Portuguese ;\nmsiegmund ; Grubbs, Deborah ; Browder, Sissel\n; Margo, Ben ; Wang, Jing (SF Associate)\n; Pierce, Naomi ; Arenas, G. Grace\n; Davidson, Nancy Fronda- \nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nEXT - tlaiche@susmangodfrey.com\n\n\nCounsel,\n\nDell was diTerently situated because it is principally a reseller of NVIDIA products. Google\u2019s own\ncon\ufb01gurations and use of NVIDIA hardware and software are far more relevant to the infringement\nissues in this case.\n\nThe subpoena served on Dell is attached. I assume the transcript you referenced is from the\nSeptember 8, 2025 discovery conference before Judge Gilliland where NVIDIA stated at the\nhearing that NAI must seek discovery from NVIDIA\u2019s customers to understand how NVIDIA\u2019s\nsource code is con\ufb01gured and used. That hearing was sealed, so we cannot provide the actual\ntranscript.\n\nWe appreciate that Google is investigating the topics addressed in the proposed declaration. We\nare willing to accept an appropriately complete declaration in lieu of document production and a\ndeposition, but we cannot agree in advance that any declaration Google elects to provide\u2014\nregardless of its scope or contents\u2014will necessarily satisfy all of Google\u2019s obligations under the\nsubpoenas. Once Google provides its proposed edits to the declaration I shared we can promptly\nassess whether it adequately addresses the relevant issues and eliminates the need for further\ndiscovery.\n\nGiven the August 11 fact-discovery deadline, however, an update sometime next week is\ninsuTicient. Please provide Google\u2019s proposed declaration, or at minimum a substantive update\nidentifying what Google is prepared to address by 4:00 pm CT on Monday so the parties can\ndetermine whether motion practice can be avoided.\n\nRegards,\n\nTanner Laiche\nSusman Godfrey LLP\n206.505.3816 | tlaiche@susmangodfrey.com\n401 Union Street | Suite 3000 | Seattle, WA 98101\nHOUSTON \u2022 LOS ANGELES \u2022 SEATTLE \u2022 NEW YORK\n\n\nFrom: JaTe, Jordan \n\n 6 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 8 of 13\n\n\nDate: Thursday, August 6, 2026 at 9:03 AM\nTo: Tanner Laiche ; Rocco Magni\n; Desai, Neil \nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; max@ciccarellilaw\ufb01rm.com ;\nTamar Lusztig ; Emily Portuguese\n; msiegmund ; Grubbs,\nDeborah ; Browder, Sissel ; Margo, Ben\n; Wang, Jing (SF Associate) ; Pierce, Naomi\n; Arenas, G. Grace ; Davidson, Nancy Fronda-\n\nSubject: RE: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\nEXTERNAL Email\nTanner,\nNon-Party Google provided its objections on July 21, 2026. Those objections explained, among\nother things, how the subpoena requests and topics were overbroad, unduly burdensome and not\nproportional to the needs of the case. As things currently stand, Neural AI has not narrowed the\nscope of any of its requests. Instead, Neural AI has provided a \u201ctemplate\u201d declaration and,\nyesterday August 4, provided additional \u201cquestions.\u201d These documents are similarly overbroad\nand unduly burdensome for a third party.\nWe also discussed on the last meet and confer providing a transcript from the hearing with Judge\nGilliland and the subpoena to Dell. We have not received that, but instead noticed that Judge\nGilliland issued an order yesterday rejected many of Neural AI\u2019s overbroad requests to Dell.\nDespite this, Google is investigating the topics covered in the \u201ctemplate\u201d declaration. Google may\nbe able to provide a declaration within a more reasonable scope. Any declaration would be\nsubject to an agreement that such a declaration satis\ufb01es all of Google\u2019s obligations under the\nsubpoenas. That includes that Google will not be required to sit for a deposition. Please con\ufb01rm.\nWe expect to have an update on the investigation next week. Given the above, we do not believe a\nmotion to compel would be a productive use of resources.\nWe\u2019re available to meet and confer further if helpful.\nBest regards,\n\n\nJordan R. JaTe | Partner | Wilson Sonsini Goodrich & Rosati\nOne Market Plaza, Spear Tower, Suite 3300 | San Francisco, CA 94105\n415.498.0556 | jjaTe@wsgr.com | LinkedIn\n\n\nFrom: Tanner Laiche \nSent: Tuesday, August 4, 2026 11:27 AM\nTo: Rocco Magni ; Jaffe, Jordan ; Desai, Neil\n\nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; max@ciccarellilawfirm.com; Tamar Lusztig\n; Emily Portuguese ;\nmsiegmund ; Grubbs, Deborah ; Browder, Sissel\n; Margo, Ben ; Wang, Jing (SF Associate)\n; Pierce, Naomi ; Arenas, G. Grace\n\n\n 7 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 9 of 13\n\n\n; Davidson, Nancy Fronda- \nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nEXT - tlaiche@susmangodfrey.com\n\n\nCounsel,\n\nI am following up on this thread.\n\nDespite the parties\u2019 prior meet-and-confers, document discovery in the underlying action closes\non August 11. Unless the parties can promptly reach a resolution, that deadline leaves Neural AI\nno practical alternative but to move to compel by the end of this week or, at the latest, August 10,\nto preserve its rights.\n\nTo reduce burden and potentially avoid motion practice, I am attaching a set of questions intended\nto guide your investigation and help identify the responsive information, and also recirculating the\ndraft declaration we previously shared, and that Google may revise to ensure its accuracy.\n\nIf Google commits to provide an executed declaration, Neural AI is willing to consider accepting\nthe declaration in lieu of further document production and/or deposition testimony, subject to\nresolving any material gaps. Otherwise, the discovery deadline will force Neural AI to move to\ncompel by or before August 10 to preserve its rights. Even if a motion becomes necessary, we\nremain open to resolving the issues promptly and mooting or withdrawing the motion through\ncompliance.\n\nWe are available this week to further meet and confer as necessary.\n\nRegards,\n\nTanner Laiche\nSusman Godfrey LLP\n206.505.3816 | tlaiche@susmangodfrey.com\n401 Union Street | Suite 3000 | Seattle, WA 98101\nHOUSTON \u2022 LOS ANGELES \u2022 SEATTLE \u2022 NEW YORK\n\n\nFrom: Rocco Magni \nDate: Tuesday, July 28, 2026 at 4:29 PM\nTo: JaTe, Jordan ; Desai, Neil \nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; Tanner Laiche ;\nmax@ciccarellilaw\ufb01rm.com ; Tamar Lusztig\n; Emily Portuguese ;\nmsiegmund ; Grubbs, Deborah ; Browder,\nSissel ; Margo, Ben ; Wang, Jing (SF Associate)\n; Pierce, Naomi ; Arenas, G. Grace\n\n 8 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 10 of 13\n\n\n; Davidson, Nancy Fronda- \nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\nJordan,\n\nPlease see attached template. Could we talk at 9:30 instead? I have another meeting at 10 now.\n\nThanks very much.\n\n--\nRocco F. Magni\nPartner | Susman Godfrey LLP\nOffice: 713.653.7861\nCell: 512.514.3519\nFirm Bio\nThis e-mail may contain privileged and confidential information. If you received this message in error,\nplease notify the sender and delete it immediately.\nFrom: JaTe, Jordan \nDate: Monday, July 27, 2026 at 2:42 PM\nTo: Rocco Magni ; Desai, Neil \nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n; Tanner Laiche ;\nmax@ciccarellilaw\ufb01rm.com ; Tamar Lusztig\n; Emily Portuguese ;\nmsiegmund ; Grubbs, Deborah ; Browder,\nSissel ; Margo, Ben ; Wang, Jing (SF Associate)\n; Pierce, Naomi ; Arenas, G. Grace\n; Davidson, Nancy Fronda- \nSubject: RE: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\nEXTERNAL Email\nRocco et al.,\n\nThanks for speaking with us last Friday. As discussed, we are waiting on you all to send over a list\nof questions for our client and/or template declaration for us to review. We will plan to reconvene\nFriday at 10AM PT to discuss further.\n\nBest regards,\n\n\nJordan R. JaTe | Partner | Wilson Sonsini Goodrich & Rosati\nOne Market Plaza, Spear Tower, Suite 3300 | San Francisco, CA 94105\n415.498.0556 | jjaTe@wsgr.com | LinkedIn\n\n\nFrom: Rocco Magni \nSent: Wednesday, July 22, 2026 4:18 AM\nTo: Desai, Neil \nCc: McKone, Mercedes ; Max Tribble ;\nBrian Melton ; Samuel Drezdzon\n\n\n 9 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 11 of 13\n\n\n; Tanner Laiche ;\nmax@ciccarellilawfirm.com; Tamar Lusztig ; Emily Portuguese\n; msiegmund ; Jaffe, Jordan\n; Grubbs, Deborah ; Browder, Sissel\n; Margo, Ben ; Pierce, Naomi ;\nArenas, G. Grace ; Davidson, Nancy Fronda- \nSubject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\nEXT - rmagni@susmangodfrey.com\n\n\nThat works. Thanks.\n--\nRocco F. Magni\nPartner | Susman Godfrey LLP\nOTice: 713.653.7861\nCell: 512.514.3519\n\nFirm Bio\n\nThis e-mail may contain privileged and con\ufb01dential information. If you received this message in\nerror, please notify the sender and delete it immediately.\n\n\n\n On Jul 21, 2026, at 11:54 PM, Desai, Neil wrote:\n\n EXTERNAL Email\n Rocco,\n\n How about Friday at 11 am PT?\n\n Neil Desai | Wilson Sonsini\n T 323.210.2912 | ndesai@wsgr.com\n\n From: Rocco Magni \n Sent: Tuesday, July 21, 2026 2:15 PM\n To: McKone, Mercedes \n Cc: Max Tribble ; Brian Melton\n ; Samuel Drezdzon ;\n Tanner Laiche ; max@ciccarellilawfirm.com; Tamar\n Lusztig ; Emily Portuguese\n ; msiegmund ; Jaffe,\n Jordan ; Desai, Neil ; Grubbs, Deborah\n ; Browder, Sissel ; Margo, Ben\n ; Pierce, Naomi ; Arenas, G. Grace\n ; Davidson, Nancy Fronda- \n Subject: Re: Neural AI, LLC v. Nvidia Corporation (C.A. 7:24-cv-00221-ADA-DTG)\n\n EXT - rmagni@susmangodfrey.com\n\n 10 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 12 of 13\n\n\n\n\nPlease provide times Friday to meet and confer. Thanks.\n--\nRocco F. Magni\nPartner | Susman Godfrey LLP\nOTice: 713.653.7861\nCell: 512.514.3519\n\nFirm Bio\n\nThis e-mail may contain privileged and con\ufb01dential information. If you received this\nmessage in error, please notify the sender and delete it immediately.\n\n\n\n On Jul 21, 2026, at 5:13 PM, McKone, Mercedes \n wrote:\n\n EXTERNAL Email\n Counsel:\n\n Please see the attached for electronic service.\n\n Thank you.\n\n \n\n Mercedes N. McKone | Executive Assistant | Wilson Sonsini Goodrich & Rosati\n 12235 El Camino Real | San Diego, CA 92130 | direct: 858.350.2217 | mmckone@wsgr.com\n \n\n\n\n\n \n\n\n\n\n This email and any attachments thereto may contain private, con\ufb01dential,\n and privileged material for the sole use of the intended recipient. Any\n review, copying, or distribution of this email (or any attachments thereto)\n by others is strictly prohibited. If you are not the intended recipient, please\n contact the sender immediately and permanently delete the original and\n any copies of this email and any attachments thereto.\n <2026-07-21 Responses and Objections to Deposition Subpoena.pdf>\n <2026-07-21 Responses and Objections to Document Subpoena.pdf>\n\n\n\nThis email and any attachments thereto may contain private, con\ufb01dential, and\n\n\n 11 of 12\n\f Case 7:26-mc-00324 Document 1-21 Filed 08/18/26 Page 13 of 13\n\n\n privileged material for the sole use of the intended recipient. Any review, copying, or\n distribution of this email (or any attachments thereto) by others is strictly prohibited. If\n you are not the intended recipient, please contact the sender immediately and\n permanently delete the original and any copies of this email and any attachments\n thereto.\n\n\n\nThis email and any attachments thereto may contain private, con\ufb01dential, and privileged material\nfor the sole use of the intended recipient. Any review, copying, or distribution of this email (or any\nattachments thereto) by others is strictly prohibited. If you are not the intended recipient, please\ncontact the sender immediately and permanently delete the original and any copies of this email\nand any attachments thereto.\n\n\nThis email and any attachments thereto may contain private, con\ufb01dential, and privileged material\nfor the sole use of the intended recipient. Any review, copying, or distribution of this email (or any\nattachments thereto) by others is strictly prohibited. If you are not the intended recipient, please\ncontact the sender immediately and permanently delete the original and any copies of this email\nand any attachments thereto.\n\n\nThis email and any attachments thereto may contain private, con\ufb01dential, and privileged material\nfor the sole use of the intended recipient. Any review, copying, or distribution of this email (or any\nattachments thereto) by others is strictly prohibited. If you are not the intended recipient, please\ncontact the sender immediately and permanently delete the original and any copies of this email\nand any attachments thereto.\n\n\nThis email and any attachments thereto may contain private, con\ufb01dential, and privileged material\nfor the sole use of the intended recipient. Any review, copying, or distribution of this email (or any\nattachments thereto) by others is strictly prohibited. If you are not the intended recipient, please\ncontact the sender immediately and permanently delete the original and any copies of this email\nand any attachments thereto.\n\n\nThis email and any attachments thereto may contain private, confidential, and privileged material for the\nsole use of the intended recipient. Any review, copying, or distribution of this email (or any attachments\nthereto) by others is strictly prohibited. If you are not the intended recipient, please contact the sender\nimmediately and permanently delete the original and any copies of this email and any attachments\nthereto.\n\n\n\n\n 12 of 12\n\f","ocr_status":1,"date_upload":"2026-08-19T03:50:45.127013-07:00","document_number":"1","attachment_number":21,"pacer_doc_id":"181037219916","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 20","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514535/","id":490514535,"tags":[],"absolute_url":"/docket/74667129/1/22/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.232428-07:00","date_modified":"2026-08-23T08:26:25.776852-07:00","sha1":"adb565f6375b1ca03ef721a1a9ec4a8537ea740d","page_count":5,"file_size":86535,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.22.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.22.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"Case 7:26-mc-00324-DC Document 1-22 Filed 08/18/26 Page 1 of 5\n\n\n\n\n EXHIBIT\n\n 21\n\f Case 7:26-mc-00324-DC Document 1-22 Filed 08/18/26 Page 2 of 5\n\n\n\n\n UNITED STATES DISTRICT COURT\n WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\n\n NEURAL AI, LLC\n\n Plaintiff, Case No. 7:24-cv-00221-ADA-DTG\n v. JURY TRIAL DEMANDED\n NVIDIA CORPORATION\n\n Defendant.\n\n\n\n\n I, [DECLARANT NAME], hereby declare as follows:\n\n 1. I am [TITLE] of [COMPANY NAME]. I am over the age of eighteen and\n\ncompetent to make this declaration. I make this declaration based on my personal knowledge,\n\nincluding my general familiarity with [COMPANY NAME]\u2019s technical infrastructure, software\n\ndeployments, use of NVIDIA products, as well as the on the basis of a reasonably diligent\n\ninvestigation.\n\n 2. I understand that this declaration is submitted in connection with a subpoena served\n\non [INSERT DAT] on [COMPANY NAME] in the above-captioned action (the \u201cSubpoena\u201d).\n\n 3. In the ordinary course of business, [COMPANY NAME] uses NVIDIA GPUs (as\n\nthat term is defined in the Subpoena attached as Exhibit A) in its commercial operations.\n\nSpecifically, [COMPANY NAME] deploys GPUs of the [INSERT ARCHITECTURE]\n\narchitecture(s), including but not limited to [INSERT SPECIFIC GPU MODEL(S)] (collectively,\n\nthe \u201cDeployed NVIDIA GPUs\u201d).\n\n 4. In the ordinary course of business, [COMPANY NAME] uses the following\n\nNVIDIA offerings in connection with the Deployed NVIDIA GPUs: [Select among cuFFT,\n\f Case 7:26-mc-00324-DC Document 1-22 Filed 08/18/26 Page 3 of 5\n\n\n\n\ncuSparse, cuSolver, cuBlas, and cuDNN].\n\n 5. In the ordinary course of business, [COMPANY NAME] uses the following\n\nNVIDIA offerings in connection with the Deployed NVIDIA GPUs: [Select PyTorch and/or\n\nTensorRT].\n\n 6. In the ordinary course of business, [COMPANY NAME] uses the following\n\nNVIDIA offerings in connection with the Deployed NVIDIA GPUs: [Select among Modulus,\n\nMaxine, cuQuantum, Merlin, Ariel, Monai, Triton, Nemo, Riva, Metropolis, Holoscan, Clara\n\nParabricks, Rapids, Issac, Drive, and Morpheus].\n\n 7. In the ordinary course of business, [COMPANY NAME] uses the NVIDIA\n\nsoftware identified in Paragraphs 4-6 as provided by NVIDIA, without modification to the source\n\ncode.\n\n 8. To the best of [COMPANY NAME]\u2019s knowledge, when it uses the NVIDIA\n\nSoftware on the Deployed NVIDIA GPUs in the ordinary course of business, the hardware and\n\nNVIDIA software function together as designed and intended by NVIDIA.\n\n 9. In the ordinary course, [COMPANY NAME] uses one or more pretrained neural-\n\nnetwork models, model implementations, or model configurations distributed, made available, or\n\nrecommended by NVIDIA. In the ordinary course, [COMPANY NAME] deploys those models,\n\nimplementations, or configurations using PyTorch, TensorRT, or other NVIDIA software without\n\nmodifying their underlying network structure or low-level implementation code.\n\n 10. In the ordinary course of business, the Deployed NVIDIA GPUs are installed in\n\nsystems with separate CPU main memory and GPU memory, and the CPU and GPU in these\n\nsystems are connected via a bus.\n\n 11. In the ordinary course of business and for the operations described in this\n\f Case 7:26-mc-00324-DC Document 1-22 Filed 08/18/26 Page 4 of 5\n\n\n\n\ndeclaration, [COMPANY NAME] may use does not use Deployed NVIDIA GPUs with [SELECT\n\nTHOSE THAT APPLY: a unified CPU/GPU memory pool, GPUDirect Storage (\u201cGDS\u201d) to\n\ntransfer input data directly from storage to GPU memory, NVIDIA Unified Virtual Memory\n\n(\u201cUVM\u201d), or CUDA managed memory]. In such configurations, a CPU is nevertheless used in\n\nconnection with operation of the GPU(s), including to initiate model inference and/or to pass input\n\ndata to or otherwise interact with the machine-learning model being run on the GPU(s). to bypass\n\nthe standard CPU-memory-to-GPU-memory data transfer path.\n\n 12.11. In [COMPANY NAME]\u2019s normal operations, when it uses the NVIDIA software\n\ndescribed in Paragraphs 4-6 on the Deployed NVIDIA GPUs, input data is received and processed\n\nby the CPU and stored in CPU main memory before being transferred to the GPU for computation.\n\nTo the best of my knowledge, this is the default and standard method by which data is loaded for\n\nprocessing on NVIDIA GPUs.\n\n 13.12. In the ordinary course of business and to the best of [COMPANY NAME]\u2019s\n\nknowledge, [COMPANY NAME] does not implement custom code or configurations that alter\n\nthe default data flow path provided by the NVIDIA Software with respect to how input data is\n\nreceived by the CPU, stored in main memory, and transferred to the GPU for computation.\n\n 14.13. To the best of [COMPANY NAME]\u2019s knowledge, the operations described in this\n\ndeclaration are performed in the United States using systems located in the United States or\n\nsystems that directly support [COMPANY NAME]\u2019s United States operations.\n\n 15.14. At least once per day, [COMPANY NAME] uses NVIDIA GPUs in conjunction\n\nwith at least one NVIDIA offering identified in each of Paragraphs 4-6.\n\n I declare under penalty of perjury under the laws of the United States of America that the\n\nforegoing is true and correct. Executed on [DATE], in [CITY, STATE].\n\f Case 7:26-mc-00324-DC Document 1-22 Filed 08/18/26 Page 5 of 5\n\n\n\n\n_______________________________________\n[DECLARANT NAME]\n[TITLE]\n[COMPANY NAME]\n\f","ocr_status":1,"date_upload":"2026-08-20T10:56:19.572809-07:00","document_number":"1","attachment_number":22,"pacer_doc_id":"181037219917","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Exhibit 21","acms_document_guid":""},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490514536/","id":490514536,"tags":[],"absolute_url":"/docket/74667129/1/23/neural-ai-llc-v-google-inc/","date_created":"2026-08-19T03:49:13.243273-07:00","date_modified":"2026-08-23T02:44:10.158377-07:00","sha1":"5ab5eebd20a85fc4501c28f0b1cc4fbc49ed159b","page_count":2,"file_size":111423,"filepath_local":"recap/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.23.pdf","filepath_ia":"https://archive.org/download/gov.uscourts.txwd.1172928145/gov.uscourts.txwd.1172928145.1.23.pdf","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":" Case 7:26-mc-00324-DC Document 1-23 Filed 08/18/26 Page 1 of 2\n\n\n\n\n IN THE UNITED STATES DISTRICT COURT\n FOR THE WESTERN DISTRICT OF TEXAS\n MIDLAND/ODESSA DIVISION\n\n\n NEURAL AI, LLC,\n Misc. Case No. 7:26-mc-324\n Petitioner,\n Principal case pending in Western District of\n v. Texas, Civil Action No. 7:24-cv-00221-LS-\n DTG\n GOOGLE, LLC,\n\n Respondent.\n\n\n\n [PROPOSED] ORDER ON PETITIONER'S MOTION TO COMPEL\n COMPLIANCE WITH SUBPOENA SERVED ON THIRD-PARTY GOOGLE, LLC\n\n Before the Court is Petitioner Neural AI, LLC\u2019s Motion to Compel Compliance with\n\nSubpoena Served on Third-Party Google, LLC. Having considered the Motion, the responses and\n\nobjections thereto, and the applicable law, the Court finds that the Motion should be and hereby is\n\nGRANTED.\n\n IT IS THEREFORE ORDERED that Third-Party Google, LLC shall produce\n\nnonprivileged documents responsive to Requests for Production Nos. 1\u201312 on a rolling basis, with\n\nproduction to begin within seven (7) days of the date of this Order and be completed within twenty-\n\none (21) days of this Order.\n\n IT IS FURTHER ORDERED that Third-Party Google, LLC shall designate and produce a\n\nknowledgeable witness for deposition testimony on Deposition Topics 1\u20135 within thirty (30) days\n\nof the date of this Order.\n\n\n\n\n 1\n\f Case 7:26-mc-00324-DC Document 1-23 Filed 08/18/26 Page 2 of 2\n\n\n\n\nSO ORDERED: this _____ day of _____________________, 2026.\n\n\n\n\n United States District Judge\n\n\n\n\n 2\n\f","ocr_status":1,"date_upload":"2026-08-20T10:56:20.414541-07:00","document_number":"1","attachment_number":23,"pacer_doc_id":"181037219918","is_available":true,"is_free_on_pacer":null,"is_sealed":null,"document_type":2,"description":"Proposed Order","acms_document_guid":""}],"date_created":"2026-08-18T17:13:30.477168-07:00","date_modified":"2026-08-19T03:48:57.392781-07:00","date_filed":"2026-08-18","time_filed":"18:30:09","entry_number":1,"recap_sequence_number":"2026-08-18.001","pacer_sequence_number":3,"description":"MOTION to Compel Compliance with Subpoena Served on Third-Party Google, LLC by Neural AI, LLC. (Attachments: # 1 Affidavit of Tanner Laiche, # 2 Exhibit 1, # 3 Exhibit 2, # 4 Exhibit 3, # 5 Exhibit 4, # 6 Exhibit 5, # 7 Exhibit 6, # 8 Exhibit 7, # 9 Exhibit 8, # 10 Exhibit 9, # 11 Exhibit 10, # 12 Exhibit 11, # 13 Exhibit 12, # 14 Exhibit 13, # 15 Exhibit 14, # 16 Exhibit 15, # 17 Exhibit 16, # 18 Exhibit 17, # 19 Exhibit 18, # 20 Exhibit 19, # 21 Exhibit 20, # 22 Exhibit 21, # 23 Proposed Order)(Magni, Rocco) (Entered: 08/18/2026)","tags":[]},{"resource_uri":"https://www.courtlistener.com/api/rest/v4/docket-entries/474970627/","id":474970627,"docket":"https://www.courtlistener.com/api/rest/v4/dockets/74667129/","recap_documents":[{"resource_uri":"https://www.courtlistener.com/api/rest/v4/recap-documents/490487424/","id":490487424,"tags":[],"absolute_url":"","date_created":"2026-08-18T17:13:27.276417-07:00","date_modified":"2026-08-18T17:13:27.276445-07:00","sha1":"","page_count":null,"file_size":null,"filepath_local":null,"filepath_ia":"","ia_upload_failure_count":null,"thumbnail":null,"thumbnail_status":0,"plain_text":"","ocr_status":null,"date_upload":null,"document_number":"","attachment_number":null,"pacer_doc_id":"","is_available":false,"is_free_on_pacer":null,"is_sealed":null,"document_type":1,"description":"Payment of Miscellaneous Filing Fee","acms_document_guid":""}],"date_created":"2026-08-18T17:13:27.262718-07:00","date_modified":"2026-08-18T17:13:27.262736-07:00","date_filed":"2026-08-18","time_filed":"18:37:48","entry_number":null,"recap_sequence_number":"2026-08-18.001","pacer_sequence_number":null,"description":"","tags":[]}],"entries_total":"https://www.courtlistener.com/api/rest/v4/docket-entries/?count=on&docket=74667129&page_size=40"}