Every second, businesses worldwide are making critical decisions. A logistics company decides which trucks to send where. A retailer figures out how to stock its shelves. An airline scrambles to reroute flights after a storm. These aren’t just routing choices — they’re high-stakes puzzles with millions of variables, and getting them wrong costs money and,

Scientists and engineers of all kinds are equipped to solve tough problems a lot faster with NVIDIA CUDA-X libraries powered by NVIDIA GB200 and GH200 superchips. Announced today at the NVIDIA GTC global AI conference, developers can now take advantage of tighter automatic integration and coordination between CPU and GPU resources — enabled by CUDA-X

Physical AI is unlocking new possibilities at the intersection of autonomy and robotics — accelerating, in particular, the development of autonomous vehicles (AVs). The right technology and frameworks are crucial to ensuring the safety of drivers, passengers and pedestrians. That’s why NVIDIA today announced NVIDIA Halos — a comprehensive safety system bringing together NVIDIA’s lineup

AI is now mainstream and driving unprecedented demand for AI factories — purpose-built infrastructure dedicated to AI training and inference — and the production of intelligence. Many of these AI factories will be gigawatt-scale. Bringing up a single gigawatt AI factory is an extraordinary act of engineering and logistics — requiring tens of thousands of

Under the hood of every AI application are algorithms that churn through data in their own language, one based on a vocabulary of tokens. Tokens are tiny units of data that come from breaking down bigger chunks of information. AI models process tokens to learn the relationships between them and unlock capabilities including prediction, generation