Google DeepMind unveiled a way to train advanced AI models across distributed data centers. Known as decoupled distributed low-communication (DiLoCo), the architecture isolates local disruptions such ...

Enterprise AI workloads require infrastructure designed for large-scale data processing and distributed computing. Organizations are modernizing AI data center infrastructure with GPU computing, ...

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 ...

The future of enterprise architecture isn’t cloud-first — it’s intelligence-first. And the shift is already underway.

In a recent article, “The Rise Of Distributed Data Centers In The AI Era,” I explored why enterprises are moving beyond a single, centralized data center to a fabric of compact, powerful data centers ...

AI is inspiring organizations to rethink a fundamental IT concept: the data center. For decades, the data center was a centralized place. It was a handful of large, secure facilities where ...

Data centers may be coming to your neighborhood as side installations associated with new homes—and in exchange would offer ...

Dave McCarthy, Research Vice President for Cloud and Infrastructure Services at IDC, joins SDxCentral’s Kat Sullivan to discuss how the AI cloud stack is evolving as companies move from model training ...

In December, several figures in the AI field, including Lado Okhotnikov, argued that decentralised AI could offer an ...