arXiv AI By Gianluca Guidi, Francesca Dominici

The Hidden Water Geography of U.S. Hyperscale Data Centers in the AI Era

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arXiv:2607. 02531v1 Announce Type: cross Abstract: Water use by data centers is routinely reported as a single footprint, but water is consumed through two physically distinct pathways: at the site for cooling and in the power system that generates electricity.

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Artificial Intelligence for Energy Optimization in Data Centers

The paper reviews 194 papers on using artificial intelligence to optimize data center energy use, coding 63 of them. It finds that most control studies validate only in simulation, none consider water withdrawal or embodied carbon, and savings estimates overlap across methods, preventing ranking. The authors propose CLEAR‑DC, a framework that links control and workload demand through elasticity, reports net benefits, and records energy, carbon, water, embodied share, and validation venue.

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Assessing the Carbon Emissions and Energy Consumption of U.S. Hyperscale Data Centers

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InFactPlanner: Planning Sustainable Geo-Distributed LLM Data Centers

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