Nvidia Corp. is broadening its physical AI collaborations with major South Korean manufacturers and chipmakers, pairing its simulation, robotics, and accelerated-computing platforms with partners spanning automotive, semiconductor, electronics, and autonomous-driving sectors1,3,5.
The partnerships were detailed at Nvidia AI Day Seoul 2026, held at COEX in Seoul's Gangnam District on November 94. Deepu Talla, Nvidia's vice president of Robotics and Edge AI, said in a keynote that Korea has consistently performed beyond expectations in heavy industry, automotive, and electronics manufacturing, and that Korea will play a key role in the development of physical AI over the next 10 years.
Semiconductor simulation gains
Samsung Electronics is using Nvidia computing tools to improve semiconductor research and engineering, including materials analysis, manufacturing process simulations, and device development. Samsung reported a roughly 1,600-fold speedup in one semiconductor simulation using AI and GPU acceleration, reducing processing time from about 18 hours to 41 seconds with a less detailed simulation grid. SK hynix is also collaborating with Nvidia to accelerate semiconductor R&D simulations; using Nvidia's PhysicsNeMo tool, SK hynix developed an AI model that predicts how a material's shape changes as it is etched away.
Nvidia introduced NVLink Fusion, a strategy to integrate custom AI semiconductors into its data center infrastructure, and said the technology will help custom-chip developers tap into the existing AI infrastructure ecosystem and shorten time to market. Nvidia also introduced DSX, a platform that treats an entire data center as a single computer and optimizes GPUs, networking, cooling, and power delivery.
Robotics and factory deployment
LG trained Nvidia's GR00T robot AI model on the movements of skilled workers and simulation data, and demonstrated manufacturing tasks using its CLOiD robot powered by Nvidia's Isaac GR00T models. LG deployed and tested a humanoid robot in a process involving hanging a washing machine top panel weighing about 4 kg on a hanger. LG used Nvidia's Cosmos to generate training data featuring a range of backgrounds and applied TensorRT to physical robots to increase inference speed. LG recreated production processes in a virtual environment to validate robot movements before factory deployment.
Doosan Robotics and Nvidia are developing robot technology that precisely polishes auto body surfaces, while Hyundai Motor Group and Nvidia are working to implement auto production plants as digital twins. Nvidia said that by using AI agent technology, the time to build simulation environments for robot development can be cut from several months to within a week.
Autonomous driving and AI model development
Kakao Mobility plans to integrate Nvidia technology into a Level 4 autonomous driving system. SK Telecom, LG AI Research, and Upstage are using Nvidia's Nemotron technology and datasets to develop AI models tailored to Korean and local industry needs. Nvidia is also expanding ties with Korean AI companies through the Nemotron Coalition, a partnership for open AI model development with Naver.
Nvidia introduced Switchyard, a technology that selects appropriate models based on task difficulty and cost; internal tests showed that distributing work across multiple models cut costs to about one-third while maintaining the same 80% task success rate.
ANALYSIS The breadth of partnerships — spanning semiconductor fabrication, factory robotics, autonomous vehicles, and Korean-language AI model development — positions Nvidia's platform stack as cross-vertical infrastructure rather than a point solution for any single industry.