Physical AI

Robotics is undergoing a revolution, moving beyond the era of specialist machines to generalist robotics. This shift moves away from single-purpose,...

Open source AI models such as Cosmos, DeepSeek, Gemma, GPT-OSS, Llama, Nemotron, Phi, Qwen, and many more are the foundation of AI innovation. These models are...

Running 3D applications that take advantage of advanced rendering and simulation technologies often requires users to navigate complex installs and have access...

Turning real-world environments into interactive simulation no longer requires days or weeks of work. With NVIDIA Omniverse NuRec and 3DGUT (3D Gaussian with...

This post explores a promising direction for building dynamic digital representations of the physical world, a topic gaining increasing attention in recent...

As part of continued efforts to ensure NVIDIA Omniverse is a developer-first platform, NVIDIA will be deprecating the Omniverse Launcher on Oct. 1. Doing so...

Building smarter robots and autonomous vehicles (AVs) starts with physical AI models that understand real-world dynamics. These models serve two critical roles:...

Physical AI enables autonomous systems—think robots, self-driving cars, and smart spaces—to perceive, understand, and act intelligently in the real world....

How can an AI system understand the difference between a plausible accident and a physically impossible event? Or plan a multi-step interaction across humans,...

Training physical AI models used to power autonomous machines, such as robots and autonomous vehicles, requires huge amounts of data. Acquiring large sets of...