Originally designed to accelerate computer image processing, graphics processing units (GPUs) are specialized circuits typically used primarily for gaming. With the boom in generative AI, though ...

The company announced this week that Azure customers using Microsoft’s GPU-assisted virtual machines for their AI applications will have newer, faster-performing options later this year.

Servers built for machine learning will need a key ingredient - graphics processing units (GPUs).

Nvidia wants to extend the success of the GPU beyond graphics and deep learning to the full data science experience. Open source Python library Dask is the key to this.

The P4 GPUs are good fits to accelerate inference engines executing pre-trained machine learning algorithms, as well as deliver remote application and desktop functionality to workers in the field.

GPUs in the public cloud is just the beginning of an emerging trend. Going forward, we will see many innovations in the hardware industry that address the growing demand for Machine Learning and ...

Machine learning tasks, like image processing, are better suited running on GPUs rather than traditional CPUs. Google is now leveraging that by allowing its Cloud Platform users to attach GPUs to ...

Image recognition software usually works with a collection of about 1 million pictures, and AI scientists questioned whether merely tweaking the machine learning algorithms could return better ...