Samsung, Kakao Mobility and LG Electronics are expanding projects that use Nvidia computing for semiconductor engineering, autonomous driving and factory robotics. The collaborations show Korean industrial groups moving AI from general models into simulation and physical systems, though several deployments remain exploratory.
Samsung is applying GPU-accelerated tools to materials, process and device engineering. Nvidia says selected quantum-chemistry calculations on Samsung’s sMOL platform ran up to five times faster end to end. In one thermal and mechanical analysis case, a combination of AI-predicted material properties, a coarser grid and GPU acceleration reduced a simulation from about 18 hours on a 32-core CPU to 41 seconds. The methods differ, so those figures should not be read as a general chip-design speedup.
Kakao Mobility plans to combine its driving software and Seoul operating experience with Nvidia’s Hyperion sensor-and-compute reference platform and Halos safety technology. Initial level 4 development is planned around Kia purpose-built vehicles; a commercial service date was not announced.
LG and Nvidia have also demonstrated robotic manipulation and manufacturing tasks with LG’s CLOiD robot. Their workflow links real-world data collection, synthetic-data augmentation, GR00T training, Jetson onboard computing and simulation-based evaluation. The immediate output is a repeatable training loop, not proof that the robots can yet handle unrestricted factory work.