New distributed reinforcement learning system cuts post-training costs by up to 80%, expanding access to advanced AI beyond ...

What if you could train massive machine learning models in half the time without compromising performance? For researchers and developers tackling the ever-growing complexity of AI, this isn’t just a ...

A new generation of decentralized AI networks is moving from theory to production. These networks connect GPUs of all kinds ...

A quiet shift in the foundations of artificial intelligence (AI) may be underway, and it is not happening in a hyperscale data center. 0G Labs, the first decentralized AI protocol (AIP), in ...

For years, the most powerful artificial intelligence systems have been trained behind closed doors–inside massive data centers owned by a select few technology giants. These facilities concentrate ...

Forged in collaboration with founding contributors CoreWeave, Google Cloud, IBM Research and NVIDIA and joined by industry leaders AMD, Cisco, Hugging Face, Intel, Lambda and Mistral AI and university ...

As AI demand shifts from training to inference, decentralized networks emerge as a complementary layer for idle consumer hardware.

A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...

Enterprise AI adoption is widespread in ambition and uneven in execution. Across industries, organizations are experimenting with machine learning and generative models, training teams, and deploying ...

In the fast-changing digital era, the need for intelligent, scalable and robust infrastructure has never been so pronounced. Artificial intelligence is predicted as the harbinger of change, providing ...

RALEIGH, N.C. – Oct. 14, 2025 – Red Hat today announced Red Hat AI 3 as part of its enterprise AI platform. Bringing together the latest developments of Red Hat AI Inference Server, Red Hat Enterprise ...