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 ...

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

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 ...

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.

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

What if the key to unlocking faster, more efficient machine learning workflows lies not in your algorithms but in the hardware powering them? In the world of GPUs, where raw computational power meets ...

Meta's reported partnership with Google for AI training on TPUs has cost Nvidia billions, impacting its market value. This ...

The computing demands of modern applications, especially those making heavy use of AI, are extending pressure beyond design ...

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 ...

Retailers must adopt GPU cloud to deliver enterprise-scale, real-time personalisation on the cloud while meeting performance, security, and privacy expectations.