NVIDIA partners with LG and Doosan to build AI factories for robotics and autonomous manufacturing

NVIDIA and LG Group Build an AI Factory to Advance Physical AI, Mobility and AI Infrastructure

New AI factory to serve as the foundation for LG Group's robotics, autonomous driving, data center technologies and GPU cloud services. NVIDIA and LG Group are building an AI factory to accelerate LG Group's next wave of AI-driven businesses, spanning robotics, autonomous driving, data center technologies and GPU cloud services. The AI factory will provide LG Group with accelerated computing infrastructure to train, simulate, validate and deploy AI-based applications across its key businesses. The collaboration brings together NVIDIA's full-stack, end-to-end AI factory platform with LG Group's global leadership in consumer electronics, robotics, mobility components, smart spaces and data center technologies. Together, the companies are connecting AI model development, physical AI data generation, robot simulation and training, edge deployment and factory-scale digital twins into a unified workflow for building physical AI systems. Advancing Physical AI and Robotics The combination of LG's production technology data and know-how from global manufacturing sites with NVIDIA's AI infrastructure and digital twin technologies will help enhance AI-driven manufacturing AI competitiveness. The two companies will collaborate to build an autonomous manufacturing ecosystem in which the entire process -- from raw material procurement to production, logistics and customer delivery -- is connected in real time through data and AI, and establish it as a new global smart factory standard. LG Electronics is developing home-based robots like CLoiD to help with a wide range of indoor household tasks, enhancing everyday convenience and improving quality of life. By integrating the NVIDIA Isaac Sim and NVIDIA Isaac Lab open robotics frameworks into their development workflows, LG can simulate, train and validate these home cobots in physically accurate virtual environments before deployment. The company is exploring using the NVIDIA Isaac GR00T open, reasoning vision action language model for both its home robots and modular robotics platforms. The GR00T model will provide LG robots humanlike reasoning and the ability to execute complex tasks. NVIDIA and LG Electronics also plan to jointly develop reference robots, positioning LG's robots as part of the NVIDIA Isaac GR00T ecosystem. To help overcome the training data challenge for robotics, LG Electronics is developing a physical AI data factory poised to help Korean and global companies accelerate physical AI projects. By turning compute into data, LG will be providing high-quality training data for robotics and industrial AI projects, using NVIDIA Cosmos world foundation models for synthetic data generation and augmentation. LG Innotek, harnessing its world-class optical expertise, plans to provide state-of-the-art robotics components, including sensing solutions, specifically optimized for NVIDIA's development environments and GPU architecture. LG CNS is building an ecosystem that enables anyone to easily adopt AI robots in manufacturing and logistics sites. By integrating NVIDIA's robotics technologies including Isaac open robotics frameworks, NVIDIA Cosmos open world models and Isaac GR00T robotic foundation models into its PhysicalWorks industrial robot platform, the company is accelerating the AI transformation of logistics and manufacturing floors. Building an NVIDIA DSX-Aligned AI Factory Infrastructure The two companies will also expand cooperation in the field of next-generation AI factories, which will support the AI era. Beyond its certification cooperation with NVIDIA on cooling solutions for AI factory thermal management -- including cooling distribution units (CDUs) and cold plates -- LG Electronics is further elevating its AI factory capabilities through technical collaboration on prefabricated modular design technologies. This initiative aligns with the NVIDIA DSX AI factory platform, enabling the rapid deployment of scalable, high-performance supercomputing infrastructure. These technologies include CDUs, cold plates and prefab modular design capabilities to help address the power, thermal and deployment requirements of next-generation liquid-cooled AI factories. In collaboration with LG Electronics and LG Energy Solution, LG Uplus -- a telecommunications provider under LG Corp. -- plans to build scalable, power-efficient AI factories based on NVIDIA DSX. The effort is expected to combine NVIDIA accelerated computing and AI factory reference architectures with LG's infrastructure, energy and telecommunications capabilities to support future AI cloud and GPU service opportunities. LG CNS plans to build scalable, power-efficient, high-performance AI factories powered by NVIDIA GPUs based on NVIDIA DSX. LG Uplus plans to build a large-scale AI data center capable of accommodating the latest NVIDIA GPUs. LG Energy Solution plans to collaborate with NVIDIA on emerging 800 volt-direct-current data center energy solutions, in alignment with NVIDIA's BESS Self-Qualification guidelines, to keep pace with next-generation GPUs. Accelerating Autonomous Driving and Mobility AI In mobility, LG Electronics works with NVIDIA to align its advanced driver-assistance systems (ADAS) and in-vehicle AI systems with the NVIDIA DRIVE platform. The collaboration will focus on aligning sensor, compute and software architectures with the NVIDIA DRIVE Hyperion architecture, supporting LG Electronics' roadmap for autonomous driving, ADAS and software-defined vehicles. LG Electronics also plans to use NVIDIA DRIVE AGX accelerated compute for its future mobility applications, including AI-powered cockpits and edge AI processing. Through this work, LG Electronics aims to strengthen its automotive electronics portfolio and accelerate the development of AI-driven mobility solutions for global manufacturers. LG Innotek is rapidly cementing its leadership in the autonomous driving market, using its core portfolio of world-class sensing, connectivity and lighting solutions. LG Innotek plans to collaborate with NVIDIA on next-generation components engineered specifically for NVIDIA architecture. Advancing Sovereign AI With EXAONE NVIDIA and LG AI Research are collaborating to advance EXAONE, one of Korea's leading sovereign AI models and an open model family available to developers, enterprises and researchers. LG AI Research used NVIDIA Blackwell GPUs, NVIDIA NeMo framework and NVIDIA Nemotron open datasets to support EXAONE model development, as well as NVIDIA TensorRT-LLM software to build high-performance inference engines for optimized deployment. LG Group is exploring broader adoption of EXAONE and agentic AI technologies across its businesses through platforms such as ChatEXAONE -- LG Group's EXAONE-based enterprise chatbot service. NVIDIA will help power LG AI Research's sovereign AI models, so LG Group can accelerate enterprise AI transformation, software-defined operations and productivity across its business portfolio. Learn more about the NVIDIA DSX platform. (Image courtesy of LG Group)

NVIDIA and Doosan Group Collaborate to Advance Physical AI and AI Factory Infrastructure

Companies to explore robotics, AI factory power solutions and advanced electronics materials for next-generation data center systems. NVIDIA and Doosan Group are expanding their collaboration to advance new opportunities across physical AI, robotics and AI factory infrastructure, spanning Doosan Robotics, Doosan Bobcat, Doosan Enerbility and Doosan Corporation Electro-Materials BG. The collaboration will bring together NVIDIA's full-stack accelerated computing platforms with Doosan Group's capabilities in industrial automation, power generation and advanced electronics materials to support next-generation AI infrastructure. Doosan Group's businesses span several layers of the AI factory ecosystem, from intelligent robotics systems to the full spectrum of large-scale power solutions and advanced electronics materials for AI data center equipment. NVIDIA and Doosan will explore how NVIDIA's physical AI stack, NVIDIA DSX AI factory platform, NVIDIA MGX and accelerated computing platforms can support these areas. Advancing Physical AI and Robotics Doosan Robotics is integrating NVIDIA Isaac Sim and NVIDIA Isaac Lab open robotics frameworks, NVIDIA Cosmos open world foundation models, the open source Newton physics engine and NVIDIA Jetson Thor to advance its Agentic Robot OS -- an AI-powered platform connecting perception, reasoning, simulation, learning and on-device inference. By integrating NVIDIA's physical AI technologies, Doosan Robotics aims to help industrial robots better perceive, reason and act in complex and dynamic environments. Simulation-to-real workflows, physics calibration and AI reasoning will make collaborative robots more adaptable, task-specialized and ready for scalable deployment. The companies are also looking to develop reference use cases for high-value industrial tasks such as depalletizing and sanding, as well as new robot form factors including dual-arm and humanoid platforms. Built on Agentic Robot OS, these capabilities aim to help Doosan Robotics evolve from a robot arm provider into a full-stack AI-first robotics solution company. The work is part of a broader, Doosan Group-wide direction for physical AI that extends beyond robotics into areas such as construction machinery and power equipment. Doosan Bobcat also plans to explore integrating NVIDIA physical AI technologies into equipment used across construction, landscaping, agriculture and material handling applications. This work will help accelerate the development of specialized world models that enable Doosan Bobcat's equipment to perceive diverse operating environments, reason about changing conditions and perform tasks more autonomously. The companies also aim to help establish an industry-standard ecosystem for compact autonomous equipment. Exploring AI Factory Power Solutions Doosan Enerbility is exploring opportunities to support NVIDIA AI factories and the NVIDIA DSX AI factory platform through its large-scale power infrastructure portfolio, including gas turbines, steam turbines and small modular reactors, together with Doosan Fuel Cell's hydrogen fuel-cell systems. These technologies are relevant to AI data centers that require reliable, high efficiency and continuously available power. Future collaboration could include power supply design for AI factory deployments, optimization of generation equipment and evaluation of low-carbon power sources such as small modular reactors. By aligning AI infrastructure requirements with energy system expertise, Doosan Enerbility could help address the growing power demands of accelerated computing. Supporting the NVIDIA MGX Ecosystem With Advanced PCB Materials Doosan Corporation Electro-Materials BG is supporting next-generation AI data center infrastructure through copper clad laminate, or CCL, a key foundational material for printed circuit boards. High-performance CCLs are used in printed circuit boards (PCBs) for networking equipment, AI accelerators and AI server motherboards, where low signal loss and high reliability are critical. NVIDIA MGX provides a modular reference architecture for accelerated systems, helping system manufacturers and ecosystem partners build servers and rack-scale AI factory infrastructure. As AI servers and networking systems increase in performance and bandwidth, advanced PCB materials such as CCL can play an important role in enabling high-speed signal integrity across the data center equipment ecosystem. Learn more about NVIDIA DSX and MGX. Featured image courtesy of Doosan Group.

NVIDIA-LG Partnership: Strengthening Robotics, Automation & Advanced Computing Infrastructure

NVIDIA and South Korea's LG Group have announced a strategic partnership to develop a global AI factory. This move aims to bring advanced computing and automation technologies into manufacturing, mobility, robotics, and data center operations. The collaboration combines NVIDIA's computing platforms with LG's industrial and electronics businesses. Both companies plan to work on technologies that support factory automation, robotics, autonomous vehicles, and large-scale data processing. The announcement reflects a broader shift in the technology sector. After two years of heavy investment in generative AI tools, companies are now focusing on practical industrial applications that can improve operations and productivity.