NVIDIA and LG Group are deepening their partnership with a broad AI factory initiative aimed at speeding up work in robotics, autonomous driving, data centers and cloud services. The companies say the effort will give LG access to accelerated computing infrastructure for training, simulation, validation and deployment of AI applications across multiple businesses.
The collaboration combines NVIDIA’s full-stack AI factory platform with LG’s reach in consumer electronics, robotics, mobility components, smart spaces and data center technologies. In practice, the companies plan to connect model development, synthetic data generation, robot simulation, edge deployment and digital twins into one workflow for building physical AI systems.
A major part of the partnership centers on robotics. LG Electronics is developing home robots, including its CLoiD line, for indoor household tasks. To support that work, LG plans to integrate NVIDIA’s Isaac Sim and Isaac Lab robotics frameworks into its development process. Those tools allow robots to be simulated, trained and tested in virtual environments before they are deployed in the real world.
LG is also evaluating NVIDIA’s Isaac GR00T model, which is designed to give robots more advanced reasoning and task execution. The companies said they also intend to jointly develop reference robots, with LG aiming to place its machines within the broader Isaac GR00T ecosystem.
LG Electronics is additionally building what it calls a physical AI data factory to help address the lack of training data in robotics and industrial AI. The company plans to use NVIDIA Cosmos world foundation models for synthetic data generation and augmentation, turning compute resources into data that can be used for AI training.
Other LG units are also involved. LG Innotek plans to supply robotics components, including sensing systems optimized for NVIDIA development environments and GPU architecture. LG CNS is incorporating NVIDIA’s robotics technologies, Cosmos models and Isaac GR00T into its PhysicalWorks industrial robot platform to support manufacturing and logistics automation.
The two companies are also working on next-generation AI factory infrastructure. LG Electronics will expand its cooperation with NVIDIA on thermal management systems such as cooling distribution units and cold plates, along with prefabricated modular design techniques. The work is meant to fit NVIDIA’s DSX AI factory platform and support faster deployment of large-scale, liquid-cooled supercomputing systems.
LG Uplus, LG Group’s telecom arm, said it plans to build scalable AI factories with LG Electronics and LG Energy Solution based on NVIDIA DSX. The company expects the effort to combine NVIDIA’s accelerated computing and reference architectures with LG’s infrastructure, energy and telecom capabilities to support future AI cloud and GPU services.
LG CNS also plans to build AI factories powered by NVIDIA GPUs, while LG Uplus is planning a large AI data center that can house the latest NVIDIA chips. LG Energy Solution said it will work with NVIDIA on 800 volt direct current data center energy solutions, following NVIDIA’s self-qualification guidelines for battery energy storage systems.
In mobility, LG Electronics is aligning its advanced driver-assistance systems and in-vehicle AI work with NVIDIA DRIVE. The companies said the effort will focus on matching sensor, compute and software architectures with the DRIVE Hyperion platform, supporting software-defined vehicles, autonomous driving and AI-powered cockpit systems.
LG Innotek also plans to develop next-generation automotive components tailored to NVIDIA architecture.
The partnership extends to language models as well. NVIDIA and LG AI Research are working to advance EXAONE, which LG describes as one of South Korea’s leading sovereign AI models. LG AI Research used NVIDIA Blackwell GPUs, the NeMo framework, Nemotron datasets and TensorRT-LLM software in EXAONE development and deployment. LG Group is considering broader use of EXAONE and agentic AI across its businesses through tools such as its ChatEXAONE enterprise chatbot.
Together, the companies are positioning the effort as a way to accelerate AI adoption across manufacturing, mobility, robotics and enterprise software, while building infrastructure intended to support future industrial-scale AI systems.