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GeForce NOW Turns Up the Heat With New GeForce RTX 5080-Powered Toronto Server NVIDIA Nemotron Achieves Benchmark-Leading Performance With LangChain Deep Agents Harness AI Innovators Adopt NVIDIA Vera — Why Max Single-Threaded CPU at Scale Matters NVIDIA and Hugging Face Bring New Models and Frameworks to LeRobot for the Open Robotics Community How Open Models Are Driving AI Research How Nations Are Deploying AI for Strategic Priorities Joyride Through July With 12 Games Coming to GeForce NOW NVIDIA Unlocks AI Compute at Scale, Inviting Partners to Power the AI Infrastructure Buildout NVIDIA and Partners Build in America, for America NVIDIA BioNeMo Agent Toolkit Brings Accelerated AI to Life Sciences Researchers in Claude Science How NVIDIA’s Inference Software Stack Powers the Lowest Token Cost How Jaiveer Singh Is Helping Robots — and Developers — Move Faster Into the Omniverse: Three Workflows for Improving Vision AI Agent Accuracy With Synthetic Data and Fine-Tuning Claude Meets Blackwell Ultra: Anthropic’s Models Now Run on NVIDIA GB300 in Azure Firefly Aerospace Operates NVIDIA Jetson in Lunar Orbit for the First Time Open Models, Closed Environments: Palantir Brings Secure AI to US Agencies With NVIDIA Nemotron The Ultimate Summer Sale Pairing: Steam Sale Meets GeForce NOW Discounts NVIDIA and AWS Collaborate to Bring AI to Production at Scale How Businesses Are Building Specialized AI They Can Trust NVIDIA Powers Over 400 of the World’s 500 Fastest Supercomputers NVIDIA Brings Trusted, 24/7 AI Agents to Telecom Operations At ISC, JUPITER Shows What Exascale Science Looks Like NAIRR Science Program Reshapes Scientific Research, Powered by NVIDIA AI Infrastructure From Materials Simulation to Experimental Astronomy, New NVIDIA AI Software Unlocks Scientific Discoveries NVIDIA Vera CPU Opens the Way for Agentic Scientific AI at Los Alamos National Laboratory Eco Wave Power Turns Waves Into Watts With NVIDIA AI Infrastructure and Digital Twins Hotter Than a Hot Tub: The 45°C Breakthrough to Cool AI’s Biggest Machines How FERC’s Large-Load Interconnection Actions Help Address Grid Stress, Improve Affordability At Cannes Lions, NVIDIA Partners Reshape Advertising and Marketing With AI Sync and Stream: GeForce NOW Connects to Members’ Game Libraries Across Devices
NVIDIA and Doosan Group Collaborate to Advance Physical A...
Madison Huang · 2026-06-08 · via NVIDIA Blog

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.