GPUs, born to push pixels, evolved into the engine of the deep learning revolution and now sit at the center of the AI ...

In an exciting development in the tech industry, semiconductor giant Nvidia has announced a strategic partnership with burgeoning AI startup ...

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 ...

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 ...

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.

By choosing a provider with dedicated GPU resources and predictable pricing, you can eliminate a big barrier to effective AI ...

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.

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

TL;DR: The RTX PRO 6000 GPU is a powerful workstation card featuring 96GB of GDDR7 memory and 24,064 CUDA cores, designed for AI, deep learning, and scientific computing. Its advanced cooling and full ...

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 ...