Investment in large-scale AI has accelerated the development of electrical equipment, which creates opportunities for data center designers and operators to rethink power architectures.
Data from Uptime Intelligence's giant data center analysis indicates that proposed power capacity and investment tied to giant data centers and campuses are at unprecedented levels.North America represents 80% of all planned power identifed in 2025…
DLC was developed to handle high heat loads from densified IT. True mainstream DLC adoption remains elusive; it still awaits design refinements to address outstanding operational issues for mission-critical applications.
Uptime Intelligence looks beyond the more obvious trends of 2026 and examines some of the latest developments and challenges shaping the data center industry.
The updated model projects a doubling of power consumption by the end of 2026, with IT loads serving generative AI workloads breaking through 10 GW of capacity.
Financial institutions are embracing public cloud for some mission-critical workloads, and using it as a launchpad for AI development.
Consensus is growing that a major market "correction" is coming: while some infrastructure operators are highly exposed, others may stand to benefit.
As IT organizations embrace AI, data center facilities and colocation providers need to plan to deploy the supporting infrastructure - despite many uncertainties. Most, however, are still moving cautiously.
Research into neuromorphic computing could lead to the creation of smaller, faster and more energy-efficient AI accelerators. This would have a transformative impact on digital infrastructure.
AI is changing how data centers operate, what began with algorithmic fine-tuning of chilled-water plants is now moving into the IT side of operations, closer to the load. But will operators ever trust AI enough to let it run the room?
Large-scale AI training is an application of supercomputing. Supercomputing experts at the Yotta 2025 conference agree that operators need to optimize AI training efficiency and develop metrics to account for utilized power.
By raising debt, building data centers and using colos, neoclouds shield hyperscalers from the financial and technological shocks of the AI boom. They share in the upside if demand grows, but are burdened with stranded assets if it stalls.
From on-prem AI to high-density IT, this webinar examined survey findings on how operators are preparing for what's next.
AWS has recently cut prices on a range of GPU-backed instances. These price reductions make it harder to justify an investment in dedicated AI infrastructure.
Several operators originally established to mine cryptocurrencies are now building hyperscale data centers for AI. How did this change happen?
Daniel Bizo
John O'Brien
Jacqueline Davis
Jay Dietrich
Douglas Donnellan
Andy Lawrence
Max Smolaks
Dr. Rand Talib
Dr. Owen Rogers