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	<title>800V DC Power &#8211; Jain.com</title>
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	<title>800V DC Power &#8211; Jain.com</title>
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		<title>LG&#8217;s 800-Volt DC Plan Shows Why Next-Gen AI Chips Need a New Power Supply Chain</title>
		<link>https://www.jain.com/nvidia-lg-group-ai-factory-physical-ai-800v-dc-power</link>
		
		<dc:creator><![CDATA[Deepak Jain]]></dc:creator>
		<pubDate>Sun, 07 Jun 2026 16:00:00 +0000</pubDate>
				<category><![CDATA[AI Infrastructure]]></category>
		<category><![CDATA[800V DC Power]]></category>
		<category><![CDATA[AI factory]]></category>
		<category><![CDATA[LG Group]]></category>
		<category><![CDATA[liquid cooling]]></category>
		<category><![CDATA[Nvidia]]></category>
		<category><![CDATA[Physical AI]]></category>
		<category><![CDATA[South Korea]]></category>
		<category><![CDATA[Sovereign AI]]></category>
		<guid isPermaLink="false">https://www.jain.com/nvidia-lg-group-ai-factory-physical-ai-800v-dc-power</guid>

					<description><![CDATA[NVIDIA and LG Group are building an AI factory for LG's robotics, self-driving and GPU cloud businesses, with LG units planning 800-volt DC power. That power plan shows next-generation AI chips are pulling battery, cooling and electrical suppliers into the GPU supply chain.]]></description>
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<div class="jain-post-main">
<section class="jain-tldr" aria-label="Plain-English summary">
<p class="jain-tldr-kicker">TL;DR · 30-second read</p>
<h2>The Short Version</h2>
<p>NVIDIA, whose chips run most of today&#8217;s artificial intelligence, is teaming up with South Korea&#8217;s LG, the maker of televisions, appliances and car parts, on a dedicated computing center for LG&#8217;s robots, self-driving technology and cloud services.</p>
<p>The surprising part is the wiring. LG&#8217;s battery arm plans to work on power systems running at 800 volts of direct current, the steady kind a battery supplies, because the newest chips are so power-hungry that the usual way of wiring these buildings is being rethought.</p>
<p>Neither company said how big it will be, what it costs or when it opens.</p>
</section>
<p>NVIDIA announced on its corporate blog on June 7, 2026 that it and LG Group are building an AI factory to underpin LG&#8217;s robotics, autonomous driving, data center technology and GPU cloud businesses. An AI factory is a data center built specifically to train and run AI models. Neither company disclosed a GPU count, power capacity, location, cost or completion date.</p>
<p>The announcement reaches across most of LG&#8217;s affiliates. LG Electronics is working on home robots, liquid-cooling hardware, prefabricated data center modules and driver-assistance systems. LG Energy Solution plans to work on 800-volt direct-current (DC) data center power. LG Uplus and LG CNS plan AI data centers built to NVIDIA&#8217;s DSX reference design. LG Innotek will supply sensors, and LG AI Research is developing its EXAONE language models.</p>
<h2>Executive Summary</h2>
<p>The headline says a single AI factory, but the substance is broader. NVIDIA is aligning nearly every part of the LG conglomerate with its platforms: the robots LG builds, the car electronics it sells to automakers, and the cooling, power and prefabricated modules that go inside AI data centers.</p>
<p>For infrastructure readers, the most consequential line is also the most technical. LG Energy Solution, the group&#8217;s battery maker, plans to work with NVIDIA on 800-volt DC data center power &#8220;to keep pace with next-generation GPUs.&#8221; That work will follow NVIDIA&#8217;s self-qualification guidelines for battery energy storage systems (BESS). LG Electronics is also working with NVIDIA on certification for its coolant distribution units and cold plates. Taken together, this shows an industrial conglomerate positioning itself as a supplier of the power and thermal layer around the chips, not only as a buyer of compute.</p>
<p>What is missing is scale. Many of the commitments are worded as plans or explorations, and none comes with a figure for capacity, investment or timing.</p>
<h2>Why 800 Volts Is the Line That Matters</h2>
<p>Most data centers today take alternating current (AC) from the grid and convert it several times: stepped down through different voltages and finally turned into the low-voltage DC that chips actually use. Each conversion loses some energy as heat, and all of a rack&#8217;s power has to travel over copper. Electrical power equals voltage multiplied by current. So for the same power, a higher voltage means a lower current. Lower current allows thinner cables, less copper, less energy lost in the wiring and fewer conversion stages. As GPU racks pack in more power, those savings become harder to ignore. The release frames LG Energy Solution&#8217;s 800-volt DC work explicitly as a way to keep pace with next-generation GPUs, and calls such systems &#8220;emerging.&#8221; In other words, this is a power architecture still being established, not an off-the-shelf product.</p>
<p>The mechanism worth noticing is who sets the specification. LG Energy Solution&#8217;s work is being lined up against NVIDIA&#8217;s own qualification guidelines for battery storage. LG Electronics already cooperates with NVIDIA on certification for coolant distribution units (CDUs, the pumps and heat exchangers that circulate liquid to the servers) and cold plates (metal blocks that sit directly on chips to carry heat away). It is also working on prefabricated modular designs aligned with NVIDIA&#8217;s DSX AI factory platform. The chip designer is defining the electrical and thermal environment its future chips need, then qualifying suppliers against it. Batteries, power distribution, coolant loops and even modular building shells are increasingly engineered to a GPU roadmap, rather than chosen independently by the data center operator. That is the supply-chain shift the title describes.</p>
<p>Several groups feel this. Electrical-equipment and battery makers must decide whether to build for 800-volt DC before the market is settled. Cooling vendors face certification against a chip vendor&#8217;s reference design. Operators designing halls today for GPUs that arrive later must weigh whether AC-based distribution will still suit them. For LG, the opening is to sell this power, cooling and modular equipment into other companies&#8217; AI factories, not only its own. This is one announcement from one conglomerate, though. It shows the direction NVIDIA is pushing its partners, not how quickly the wider industry will follow.</p>
<h2>Why an Industrial Conglomerate Wants Its Own AI Factory</h2>
<p>Physical AI means AI that perceives and acts in the real world, such as robots, autonomous vehicles and automated factories. It depends heavily on compute before a single robot ships. LG plans to use NVIDIA&#8217;s Isaac Sim and Isaac Lab to train and test home robots such as CLoiD in physically accurate virtual environments. It also plans to use NVIDIA Cosmos world models to generate synthetic training data. Real-world robot data is scarce and expensive to collect, so simulation and synthetic data substitute compute for fieldwork. The release describes this as &#8220;turning compute into data.&#8221;</p>
<p>That changes what the AI factory is for. LG Electronics says its physical AI data factory is meant to serve Korean and global companies, not only LG. LG Uplus describes its planned facilities as supporting future AI cloud and GPU service opportunities. LG CNS is building its PhysicalWorks industrial robot platform on NVIDIA&#8217;s robotics stack. If those plans hold, part of this capacity becomes a product sold to others rather than an internal cost centre. Separately, LG AI Research trained its EXAONE models on NVIDIA Blackwell GPUs. EXAONE is described as one of Korea&#8217;s leading sovereign AI models, so the project also adds domestically controlled compute to Korea&#8217;s national AI ambitions.</p>
<p>There is an ambiguity here, though. The headline describes one AI factory, but the body describes LG CNS and LG Uplus each planning their own DSX-based facilities, and LG Uplus a separate large-scale AI data center. Whether this is one shared facility, several affiliate-owned sites, or a program with no fixed count is not stated. That matters to anyone trying to size its contribution to Korea&#8217;s compute base.</p>
<h2>Firm Commitments Versus Stated Direction</h2>
<p>The announcement mixes different levels of commitment, and it is worth separating them. Some items are described as already done: LG AI Research used Blackwell GPUs, NeMo and TensorRT-LLM for EXAONE, and certification cooperation on CDUs and cold plates is under way. Others are plans: 800-volt DC power work, the LG Uplus and LG CNS data centers, and jointly developed reference robots. Some are explicitly exploratory, such as LG&#8217;s use of the Isaac GR00T model and broader rollout of EXAONE across the group.</p>
<p>A few claims are aspirational by nature. The goal of establishing an autonomous manufacturing ecosystem as &#8220;a new global smart factory standard&#8221; cannot be judged from an announcement, because standards are made by adoption, not declaration. The mobility work is more concrete. LG Electronics is aligning its driver-assistance and in-vehicle systems with NVIDIA&#8217;s DRIVE Hyperion architecture and plans to use DRIVE AGX compute. For automakers already building on NVIDIA&#8217;s DRIVE platform, that could make LG&#8217;s components easier to integrate. The release does not name any automaker customers.</p>
<h2>Background</h2>
<p>NVIDIA designs the graphics processing units (GPUs) that are the most widely used chips for training and running AI models. It increasingly markets whole data center designs, which it calls AI factories, through its DSX platform. It also sells software stacks for robotics (Isaac, Cosmos, GR00T) and autonomous vehicles (DRIVE).</p>
<p>LG Group is one of South Korea&#8217;s largest conglomerates. Several of its affiliates appear in this announcement: LG Electronics (consumer electronics, robots, automotive electronics and cooling equipment), LG Energy Solution (batteries), LG Innotek (optical and sensing components), LG CNS (IT services), LG Uplus (telecommunications) and LG AI Research, which develops the EXAONE models that are part of Korea&#8217;s push for domestically controlled, or sovereign, AI.</p>
<section class="jain-sources" aria-label="Sources">
<h2>Sources</h2>
<p>Source: <a href="https://news.google.com/rss/articles/CBMibkFVX3lxTE1WZWJQbW5PdHZoZmNCbExjaVVXX25PcVlWNWlEcmMwSU9YakFyNDRoVXNRTm1tZUdIeThxaEJjMmR2NHl5TnFHbHhla2ctWGVfQldZREsxWEVYNFZCSDFLbVlONEM5dVZvVzl3czBn?oc=5">NVIDIA and LG Group Build an AI Factory to Advance Physical AI, Mobility and AI Infrastructure</a>, NVIDIA&#8217;s June 7, 2026 announcement of an AI factory and wider robotics, power, cooling and mobility collaboration with LG Group.</p>
</section>
</div>
<aside class="jain-rail">
<section class="jain-gaps" aria-label="What the release does not say">
<p class="jain-gaps-kicker">⚠ What They Aren’t Saying</p>
<h2>What the Release Doesn&#8217;t Say</h2>
<ul>
<li><strong>Scale and power:</strong> NVIDIA and LG have not said how many GPUs, how many megawatts of capacity, or which GPU generation the AI factory will use. They have also not said how much grid power has been secured or where it will come from.</li>
<li><strong>Structure and location:</strong> LG has not clarified whether this is one facility or several affiliate-owned sites (LG CNS, LG Uplus), where they will be built, or when they are expected to come online.</li>
<li><strong>Financing and ownership:</strong> Neither company has disclosed the investment involved, how it is split among LG affiliates, or whether NVIDIA has any financial stake beyond supplying technology.</li>
<li><strong>Customers:</strong> LG Uplus cites GPU cloud opportunities and LG Electronics says its physical AI data factory will serve outside companies, but no customers or contracted capacity have been named.</li>
<li><strong>800-volt DC readiness:</strong> LG Energy Solution has not said when its 800-volt DC products will be qualified, what capacity it will offer, or whether they will be used in LG&#8217;s own facilities first.</li>
<li><strong>Mobility commitments:</strong> LG Electronics has not named automakers that have adopted its DRIVE-aligned systems, or given timelines for DRIVE AGX-based products.</li>
</ul>
</section>
<section class="jain-faq">
<h2>Frequently Asked Questions</h2>
<h3>What did NVIDIA and LG Group announce?</h3>
<p>They are building an AI factory to support LG&#8217;s robotics, autonomous driving, data center technology and GPU cloud businesses. The announcement also covers joint work on cooling, 800-volt DC power, driver-assistance systems and LG&#8217;s EXAONE AI models.</p>
<h3>What is an AI factory?</h3>
<p>AI factory is NVIDIA&#8217;s term for a data center built specifically to produce AI: training models, running simulations and serving AI applications. Its design is organised around dense GPU computing, high-power electrical systems and liquid cooling.</p>
<h3>What is physical AI?</h3>
<p>Physical AI refers to AI systems that sense and act in the real world, such as robots, self-driving cars and automated factories. They are often trained in simulation and on synthetic data before being deployed on real machines.</p>
<h3>Why does 800-volt DC power matter for AI data centers?</h3>
<p>Power equals voltage times current, so a higher voltage delivers the same power with less current. That means thinner cables, less copper, lower wiring losses and fewer conversion steps. These benefits grow as GPU racks consume more power.</p>
<h3>What role does LG Energy Solution play?</h3>
<p>LG Energy Solution, LG&#8217;s battery maker, plans to collaborate with NVIDIA on emerging 800-volt DC data center energy solutions. The work follows NVIDIA&#8217;s self-qualification guidelines for battery energy storage systems and is intended to keep pace with next-generation GPUs.</p>
<h3>What cooling technology is LG Electronics contributing?</h3>
<p>LG Electronics is cooperating with NVIDIA on certification for coolant distribution units and cold plates, which move liquid to chips and carry heat away. It is also working on prefabricated modular designs aligned with NVIDIA&#8217;s DSX platform.</p>
<h3>What is NVIDIA DSX?</h3>
<p>DSX is NVIDIA&#8217;s AI factory platform and reference architecture. It is meant to help partners deploy scalable, high-performance AI data centers quickly, with aligned designs for compute, power, cooling and building modules.</p>
<h3>How big is the NVIDIA and LG AI factory?</h3>
<p>Neither company has disclosed its size. No GPU count, power capacity in megawatts, investment figure or floor area was announced, so its contribution to Korea&#8217;s total AI compute cannot yet be measured.</p>
<h3>Where and when will the AI factory be built?</h3>
<p>No location or completion date was announced. LG CNS and LG Uplus each describe plans for DSX-based AI factories, and LG Uplus plans a large-scale AI data center, but no sites or timelines were given.</p>
<h3>What is LG&#x27;s physical AI data factory?</h3>
<p>It is an LG Electronics effort to use compute and NVIDIA Cosmos world models to generate and augment high-quality training data for robotics and industrial AI. LG says it will serve both Korean and global companies.</p>
<h3>What is EXAONE?</h3>
<p>EXAONE is LG AI Research&#8217;s family of open AI models, described as one of Korea&#8217;s leading sovereign AI models. It was developed using NVIDIA Blackwell GPUs, the NeMo framework and Nemotron datasets, and it powers LG&#8217;s ChatEXAONE enterprise chatbot.</p>
<h3>How does the deal affect autonomous driving?</h3>
<p>LG Electronics is aligning its driver-assistance and in-vehicle AI systems with NVIDIA&#8217;s DRIVE Hyperion architecture and plans to use DRIVE AGX compute. LG Innotek plans sensing and connectivity components designed for NVIDIA&#8217;s architecture.</p>
<h3>Will LG sell GPU capacity to other companies?</h3>
<p>Possibly. LG Uplus says its planned AI factories will support future AI cloud and GPU service opportunities, but no customers, pricing or contracted capacity have been disclosed.</p>
<h3>What does this mean for data center operators and suppliers?</h3>
<p>It signals that NVIDIA is qualifying power, battery and cooling suppliers against its own reference designs. Operators planning facilities for future GPUs, and equipment vendors deciding whether to build for 800-volt DC, will want to track how those specifications develop.</p>
</section>
</aside>
</div>
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