Case 7:26-mc-00318-LS Document 6-14 Filed 08/18/26 Page 1 of 4 EXHIBIT 13 Case 7:26-mc-00318-LS Document 6-14 Filed 08/18/26 Page 2 of 4 Company Blog Artificial Intelligence AI Infrastructure Physical AI Gaming & Creating Industries Subscribe US  Sign In Tesla Unveils Top AV Training Supercomputer Powered by NVIDIA A100 GPUs ‘Incredible’ GPU cluster powers AI development for Autopilot and full self-driving. June 22, 2021 by Danny Shapiro 2 mins 0 Share Tackling one of the largest computing challenges of this lifetime requires larger than life computing. At CVPR this week, Andrej Karpathy, senior director of AI at Tesla, unveiled the in-house supercomputer the automaker is using to train deep neural networks for Autopilot and self-driving capabilities. The cluster uses 720 nodes of 8x NVIDIA A100 Tensor Core GPUs (5,760 GPUs total) to achieve an industry-leading 1.8 exaflops of performance. “This is a really incredible supercomputer,” Karpathy said. “I actually believe that in terms of flops, this is roughly the No. 5 supercomputer in the world.” With unprecedented levels of compute for the automotive industry at the center of its development cycle, Tesla is making it possible for NVIDIA GTC Berlin autonomous vehicle engineers to do their life’s work efficiently and at the cutting edge. Registration Is Now Open NVIDIA A100 GPUs deliver acceleration at every scale to power the world’s highest-performing data centers. Powered by the NVIDIA October 20-22 Ampere Architecture, the A100 GPU provides up to 20x higher performance over the prior generation and can be partitioned into seven Register Now GPU instances to dynamically adjust to shifting demands. Recent News Gaming GeForce NOW Shakes Up August With 26 New Games August 6, 2026 AI Into the Omniverse: How Open World Models Push the Frontier of Physical AI August 6, 2026 AI NVIDIA and Partners Build in America, for America August 5, 2026 AI Infrastructure The GPU cluster is part of Tesla’s vertically integrated autonomous driving approach, which uses more than 1 million cars already driving NVIDIA Joins NSF State and Regional AI on the road to refine and build new features for continuous improvement. Hubs Program to Expand AI Research and Education Across the US Case 7:26-mc-00318-LS Document 6-14 Filed 08/18/26 Page 3 of 4 August 4, 2026 From the Car to the Company Blog Data Center Subscribe US Tesla’s cyclical development begins in the car. A deep neural network running in “shadow mode” quietly perceives and makes predictions View All Recent News while the car is driving without actually controlling the vehicle. These predictions are recorded, and any mistakes or misidentifications are logged. Tesla engineers then use these instances to create a training dataset of difficult and diverse scenarios to refine the DNN. The result is a collection of roughly 1 million 10-second clips recorded at 36 frames per second, totaling a whopping 1.5 petabytes of data. The DNN is then run through these scenarios in the data center over and over until it operates without a mistake. Finally, it’s sent back to the vehicle and begins the process again. Karpathy said training a DNN in this manner and on such a large amount of data requires “a huge amount of compute,” which led Tesla to build and deploy the current generation supercomputer with high-performance A100 GPUs. Continuous Iteration In addition to comprehensive training, Tesla’s supercomputer gives autonomous vehicle engineers the performance needed to experiment and iterate in the development process. Karpathy said the current DNN structure the automaker is deploying allows a team of 20 engineers to work on a single network at once, isolating different features for parallel development. These DNNs can then be run through training datasets at speeds faster than what has been previously possible for rapid iteration. “Computer vision is the bread and butter of what we do and enables Autopilot. For that to work, you need to train a massive neural network and experiment a lot,” Karpathy said. “That’s why we’ve invested a lot into the compute.” Watch the full CVPR session. Categories: Driving Tags: NVIDIA DGX Transportation Comments for this thread are now closed × 0 Comments  1 Login  Share Best Newest Oldest This discussion has been closed. Subscribe Privacy Do Not Sell My Data Related News AI AI AI AI Case 7:26-mc-00318-LS Document 6-14 Filed 08/18/26 Page 4 of 4 Into the Omniverse: How Open Company Blog NVIDIA and Partners Build in AI Leaders Propose SAFE Industry Leaders Unite Subscribe US in Open World Models Push the America, for America Guidelines for Cybersecurity Secure AI Alliance for AI Safety Frontier of Physical AI Aug 5, 2026 Transparency and Security Aug 6, 2026 Aug 4, 2026 Jul 27, 2026 Follow Us      United States Privacy Policy Your Privacy Choices Terms of Service Accessibility Corporate Policies Product Security Contact Copyright © 2026 NVIDIA Corporation