Eco Wave Power, a member of the NVIDIA Inception startup program’s Sustainable Futures initiative, is developing technology — powered by NVIDIA AI infrastructure and digital twins — that converts energy from ocean waves into clean electricity using existing…

NVIDIA CUDA-X libraries, microservices and reference code accelerate AI for science.

Mission, Vision and Veritas supercomputers with Vera CPUs to advance materials simulation, scientific AI agents and molecular design.

The U.S. National Science Foundation’s NAIRR pilot program has driven innovative research across the U.S. for over 700 projects — spanning protein prediction and infectious disease outbreak management.

Europe’s first exascale supercomputer — running on NVIDIA Grace Hopper Superchips — is mapping the brain, modeling climate, advancing 6G AI and breaking records in quantum computing simulation.

The NVIDIA CUDA Core Compute Libraries (CCCL) provides delightful and efficient abstractions for CUDA developers in C++ and Python. It features: This post introduces a new group of functionality in…

Telecom operators are adopting AI across network operations, customer care, and back-office workflows, but most are still early in the journey to autonomy. In network operations, for example…

At DTW Ignite 2026, NVIDIA and its partners are showcasing the data, models, simulation and secure runtime stack enabling telcos to build more secure agentic workflows across autonomous networks and operations.

NVIDIA technologies power more than 400 of the world’s 500 fastest supercomputers — 81% of the TOP500.

NVIDIA Agent Toolkit — comprising models, tools, skills and a secure runtime — provides an open, modular foundation for building safer, faster, lower-cost digital AI coworkers that enterprises and developers can customize, specialize, control and trust.

AI scientists are emerging as a new interface for scientific computing. These agents can read papers, write code, generate hypotheses, call APIs, inspect files, and iterate on results. But science isn’…

As AI systems move from single-turn interactions to coordinated multiagent workflows, low-latency inference becomes increasingly important. Autoregressive LLMs generate tokens sequentially…

Power can account for 40% of the operating expenses (OpEx) to run an AI factory. Each watt can be spent on overhead, data ingestion, training, or generating tokens for customers. And most sites are…

Across Amazon OpenSearch and Amazon EC2, NVIDIA AI infrastructure is giving enterprises more practical paths to deploy AI at production scale.