NVIDIA isn’t building quantum computers, instead it’s using its supercomputing strengths to accelerate quantum computing ...

As enterprises seek alternatives to concentrated GPU markets, demonstrations of production-grade performance with diverse ...

The U.S. Deep Learning Chipset Market is estimated at USD 3.73 billion in 2025 and is projected to reach USD 53.62 billion by 2035, growing at a CAGR of 30.59% from 2026–2035. Rapid adoption of AI ...

Hardware fragmentation remains a persistent bottleneck for deep learning engineers seeking consistent performance.

Nvidia’s latest pitch for the future of graphics is not about more polygons or higher memory bandwidth, it is about teaching ...

NVIDIA announced that Facebook will power its next-generation computing system with the NVIDIA® Tesla® Accelerated Computing Platform, enabling it to drive a broad range of machine learning ...

Viperatech, a front-runner in cutting-edge technology solutions, is delighted to announce the availability of the newest lineup of NVIDIA’s state-of-the-art hardware for AI and deep learning machines.

NVIDIA announced immediate availability of the NVIDIA® GPU Cloud (NGC) container registry for AI developers worldwide. In just a few steps, NGC helps developers get started with deep learning ...

The rise of AI has given us an entirely new vocabulary. Here's a list of the top AI terms you need to learn, in alphabetical ...

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...