Enterprises racing to deploy generative AI often focus on models. In practice, outcomes depend on how well organizations prepare, manage, and move their data. AI-ready data platforms, vector databases ...

The expansion of large language models (LLMs) is creating a new problem for power grids: electricity demand from AI data ...

With AI workloads accelerating and power constraints intensifying, operators are being forced to rethink how data centers are ...

Arctera announced its transition to a focused SaaS operating model, removing traditional constraints on data volume, users, and environments, and enabling enterprises to apply consistent compliance ...

The skilled trades gap is no longer a future concern. In mechanical and electrical systems, the impact is already visible.

AI insiders are beginning to question whether the industry is building data centers for a future that may never fully arrive.

The contest for AI supremacy is shifting away from foundation models and toward the data infrastructure sitting beneath them, ...

Grok AI new model V9-Medium has completed training at 1.5 trillion parameters — three times the current production model — ...

Epoch AI forecasts inference compute will outpace training by 2030, with nearly half of inference shifting to ASICs and ...

Demands for privacy and sovereignty expose limits of architectures built for centralised and borderless data flows. - Data ...

Discover how organizations can avoid the data maturity trap by prioritizing metadata to ensure robust AI program success.