NVIDIA PhysicsNeMo
3 use cases using this technology
Foxconn Develops Physical AI-Enabled Smart Factories With Digital Twins
Foxconn (Hon Hai Technology Group)
Foxconn (Hon Hai Technology Group) uses physically accurate digital twins integrating NVIDIA Omniverse libraries and OpenUSD to design, deploy, and manage high-volume production facilities, including those producing NVIDIA GB200 Grace Blackwell Superchip systems. Its Fii Omniverse Digital Twin (FODT) platform creates virtual replicas of factories, enabling simulation-driven design, real-time monitoring, and optimized operations. Using NVIDIA PhysicsNeMo AI models, Foxconn achieves 150x faster computational fluid dynamics simulations for thermal analysis (minutes vs. hours). Standardized OpenUSD-based digital twin assets enable rapid migration of entire production lines between global factories (e.g., Taiwan to Mexico). Robot workcells and AGV logistics are simulated in FODT before physical deployment: complex robotic tasks such as screw tightening and cable insertion are simulated and refined with NVIDIA Isaac Sim, Isaac Lab, FoundationPose models, and NVIDIA cuMotion, while AGV path is optimized by connecting simulations with Material Control Systems and NVIDIA cuOpt. Foxconn also built video analytics AI agents with NVIDIA Metropolis and the NVIDIA AI Blueprint for video search and summarization to monitor factory floors, and developed FoxBrain, an AI platform powered by NVIDIA NeMo trained in four weeks, described as Taiwan's first large language model with advanced reasoning capabilities. Leo Guo, General Manager of Fii Robotic Group, said the company believes it can cut factory setup and planning time by about 50%.
MITRE's Federal AI Sandbox accelerates government AI research with NVIDIA DGX SuperPOD
MITRE
Nonprofit MITRE built the Federal AI Sandbox, powered by NVIDIA DGX SuperPOD, to give federal sponsors an affordable, centralized space to test and deploy AI and machine learning across domains such as weather forecasting, cybersecurity, and public benefits administration. The DGX SuperPOD delivers a 300-fold performance increase over MITRE's previous AI computing capabilities and supports thousands of researchers; MITRE is using it with NVIDIA Omniverse and NVIDIA Earth-2 to develop 1-kilometer precision weather forecasts with NOAA and the National Weather Service, plus a foundational model for cybersecurity threat analysis across 190 nations.
Israel's Meteorological Service Predicts the Weather Using NVIDIA Earth-2
Israel Meteorological Service (IMS)
The Israel Meteorological Service integrated an AI weather model called F3, powered by NVIDIA Earth-2 and NVIDIA PhysicsNeMo (including the CorrDiff neural network), into its forecasting system to achieve hyperlocal 2.5-kilometer resolution precipitation forecasts. F3 achieved 90 percent lower computational costs compared to running a classic non-AI numerical weather prediction model on a CPU cluster, delivering forecasts in minutes rather than hours, and saved 20-30 percent of the Tel Aviv-Yafo Municipality's preparedness budget for things like urban flood safety. CorrDiff was trained to emulate IMS's regional high-resolution ICON model using low-resolution ECMWF IFS input, enabling four high-resolution forecasts per day. Partners including the Israeli Police, the National Fire and Rescue Authority, the Ministry of Transportation and the National Road Company have adopted the forecasts, and IMS used F3 to issue a high-resolution flood map during a January storm that dropped 150 millimeters of rain in six hours.