
At Data Center World Power, Google’s Tom Garvens detailed how full-stack design, LVDC power, BESS, and liquid cooling are reshaping hyperscale AI while supporting local grids.
AI data centers are being redesigned to actively support electrical grids rather than simply draw power from them. As AI infrastructure expands at unprecedented pace, data centers are implementing technologies like battery energy storage systems, low-voltage direct current architectures, and liquid cooling to make their power consumption more efficient and grid-friendly. This matters because the rapid growth of AI compute demand is outpacing utility companies' ability to expand grid capacity, so hyperscale data centers must become partners in grid stability rather than competitors for constrained power resources. The approach involves optimizing entire systems from chip design through facility layout and using software to shift workloads across multiple locations to smooth power demand and reduce strain on local grids.

Under the One Big Beautiful Bill Act, data center projects in rural areas could be eligible for major tax benefits starting next year. Some hyperscalers do not seem eager to take the free cash.

The price of anything with memory is skyrocketing thanks to AI. Aging streaming devices are no exception.
NVIDIA announced a new 64GB configuration of DGX Spark — from Acer, ASUS, Dell, Gigabyte, HP and MSI — its GB10-powered desktop AI system. It gives developers a way to start with one system for local models and agents, then cluster two 64GB units for 128GB of memory across the cluster and more compute when workloads grow. The direct message is: Run open models and always-on agents on your own desk, then cluster DGX Spark system as the work grows – instead of on a metered API. The ti
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