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Amazon, Google, and Meta join Microsoft in signaling a shift: growth is now tied to power, chips, and unprecedented capital spending.

The reported Google-Anthropic deal pairs capital with a 5 GW compute commitment, shifting how AI infrastructure is financed and allocated.

New silicon and packaging could cut power, ease cooling, and strengthen security – if software and ecosystems keep pace.

Behind-the-meter data center builds, phased energization, and nuclear bets move from edge cases to core strategy.

Azure growth and a $627B backlog show AI demand outpacing power, cooling, and data center build capacity.

As AI workloads scale, cooling is evolving from a design consideration to a deployment challenge, forcing operators to adapt to rapidly rising power densities.

The acquisition of Elea Data Centers by I Squared Capital will fuel the Brazilian digital infrastructure operator’s expansion plans, according to the company’s founder.

Ferveret says fanless, waterless cooling can unlock more compute from fixed power, but deployments remain in pilot stage.

The Bloom Energy deal shifts planned New Mexico AI campus to on-site generation.

Maine has rejected a data center moratorium, but pressure on the industry shows no sign of easing.

AI is reshaping IT investments, and flexibility is key to balancing innovation with legacy systems, explains OSI Global’s David Colman.

As AI workloads scale, power limitations are increasingly driven by infrastructure timelines and system complexity, rather than generation alone.

PSC’s overhaul of We Energies’ tariff proposal marks a shift to stricter frameworks, ensuring hyperscale growth doesn’t burden existing ratepayers.

Floating and ocean-based data centers are emerging as innovative solutions to address land, power, and cooling constraints in dense coastal markets, offering efficiency gains through proximity to coastal infrastructure and water-based cooling.

A flatter topology and higher bandwidth reflect how hyperscalers are reshaping networks for large-scale AI clusters.

Verda’s latest funding round targets AI workload fragmentation, focusing on optimized infrastructure for training and inference.

Persistent memory shifts AI performance toward storage, networking, and data movement, not just GPU throughput.