Decentralized GPU networks are pitching themselves as a lower-cost layer for running AI workloads, while training the latest ...

This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.

Dubbed the "Nvidia killer," Cerebras' wafer-scale engine has reportedly crushed Nvidia's H200 in raw AI training power: 125 ...

A femtosecond laser approach could quietly alter chip cooling rules for AI hardware and quantum devices ...

With a focus on scalability, Paul Terry shares how Photonic's quantum architecture addresses industry challenges and paves ...

The launch of the Zhenwu 810E marks the latest initiative by China's Big Tech firms to develop a domestic alternative to ...

This decision represents far more than a new product launch; it is the culmination of Nvidia's push to become a one-stop silicon provider for AI and ...

Microsoft MVP Brien Posey used a real-world buildout of AI-enabled applications to show how GPU limits, physical infrastructure constraints, and cross-platform access requirements can reshape ...

NVIDIA AI is boosting productivity and creating new job opportunities across various sectors. New NVIDIA Earth-2 models are ...

Running both phases on the same silicon creates inefficiencies, which is why decoupling the two opens the door to new ...

Nvidia and Broadcom are two top picks in the AI computing space.

Features: High-performance computing is helping Space agencies and universities compress simulation cycles, train AI models faster, and enable more autonomous missions.