Nemotron 3 shows how Nvidia is using open models, tooling, and data to turn raw compute into deployable intelligence and ...

Nvidia CEO Jensen Huang credited Ilya Sutskever and two renowned computer scientists for sparking the "big bang of deep learning" and "AI revolution." ...

Nvidia's move to acquire SchedMD is not just another consolidation in the high performance computing world, it is a ...

The partnership between NASA and Nvidia didn’t start with artificial intelligence in mind. Back in 2003, when NASA approached the graphics company to create a photorealistic Mars simulation, nobody ...

Nvidia’s Deep Learning Institute (DLI) is offering free credits aimed at enhancing AI skills, but there are some caveats. To begin with, you must work for a startup. That said, its definition of a ...

Nvidia is the poster-child for today’s hype in Artificial Intelligence. Shares are trading at exceptionally high levels. Properly framing Industry Structure, particularly entry-barriers, is key to ...

TPUv7 offers a viable alternative to the GPU-centric AI stack has already arrived — one with real implications for the economics and architecture of frontier-scale training.

In this photo illustration the Nvidia logo is shown on a mobile phone against the illustration of a stock market graph illustration displayed on a computer screen Nvidia reported third-quarter revenue ...

Nvidia Americas Channel Chief Craig Weinstein tells CRN that the 2025 Nvidia Partner Network award recipients—which include multi-year winners like Mark III Systems and World Wide Technology as well ...

Nvidia and Qualcomm Ventures have joined a growing coalition of U.S. and Indian investors backing India’s deep tech startups. The group launched in September with more than $1 billion in commitments, ...

The artificial intelligence sprint is on, and not just within companies: This race is being held at a geographic level as well. The project will build on sovereign AI initiatives announced last year ...

NVIDIA Quadro RTX Tensor Cores are used primarily for speeding up general matrix-to-matrix multiplications, which are an essential part of many deep learning algorithms. These algorithms are part of ...