TL;DR · 30-second read
The Short Version
NVIDIA, whose chips run most of today’s artificial intelligence, is teaming up with South Korea’s LG, the maker of televisions, appliances and car parts, on a dedicated computing center for LG’s robots, self-driving technology and cloud services.
The surprising part is the wiring. LG’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.
Neither company said how big it will be, what it costs or when it opens.
NVIDIA announced on its corporate blog on June 7, 2026 that it and LG Group are building an AI factory to underpin LG’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.
The announcement reaches across most of LG’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’s DSX reference design. LG Innotek will supply sensors, and LG AI Research is developing its EXAONE language models.
Executive Summary
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.
For infrastructure readers, the most consequential line is also the most technical. LG Energy Solution, the group’s battery maker, plans to work with NVIDIA on 800-volt DC data center power “to keep pace with next-generation GPUs.” That work will follow NVIDIA’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.
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.
Why 800 Volts Is the Line That Matters
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’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’s 800-volt DC work explicitly as a way to keep pace with next-generation GPUs, and calls such systems “emerging.” In other words, this is a power architecture still being established, not an off-the-shelf product.
The mechanism worth noticing is who sets the specification. LG Energy Solution’s work is being lined up against NVIDIA’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’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.
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’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’ 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.
Why an Industrial Conglomerate Wants Its Own AI Factory
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’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 “turning compute into data.”
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’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’s leading sovereign AI models, so the project also adds domestically controlled compute to Korea’s national AI ambitions.
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’s compute base.
Firm Commitments Versus Stated Direction
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’s use of the Isaac GR00T model and broader rollout of EXAONE across the group.
A few claims are aspirational by nature. The goal of establishing an autonomous manufacturing ecosystem as “a new global smart factory standard” 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’s DRIVE Hyperion architecture and plans to use DRIVE AGX compute. For automakers already building on NVIDIA’s DRIVE platform, that could make LG’s components easier to integrate. The release does not name any automaker customers.
Background
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).
LG Group is one of South Korea’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’s push for domestically controlled, or sovereign, AI. Source: NVIDIA and LG Group Build an AI Factory to Advance Physical AI, Mobility and AI Infrastructure, NVIDIA’s June 7, 2026 announcement of an AI factory and wider robotics, power, cooling and mobility collaboration with LG Group.Sources