With Nvidia’s system, “heat is captured directly at the chip and transported through liquid loops operating at much higher ...

Produced by DCF and EndeavorB2B, this July 15-16 virtual conference brings together industry experts to explore cutting-edge ...

The AI Data Center Energy Performance Framework, developed by NEMA, ASHRAE, and PNNL, offers comprehensive guidelines to ...

Nvidia's Rubin liquid-cooled data center design drastically reduces water usage and energy consumption, addressing ...

Grid interconnection has emerged as a major bottleneck for transmission and distribution networks. Amber Semiconductor ...

The company says it has eliminated “pretty much all water usage” with its new liquid cooling design.

In an age where demand for AI is ever-growing, data center design is being redefined by one critical constraint: power.

Emma Strutton speaks with Adam Gough of Eaton about rising AI compute demand, rack density, DC power distribution, and ...

Erin Brockovich maps the rise of AI data centers and reveals three key risks around water, energy, and local impact every community should understand.

NEMA's Patrick Hughes explains why speed without a shared technical foundation is just risk masquerading as efficiency.

Between 2026 and 2030, adoption of AI datacenter liquid cooling systems is expected to accelerate rapidly as hyperscalers and AI infrastructure providers scale GPU-intensive AI training environments.