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Not every AI-era power saving comes from a new power plant -- Berkeley Lab reported in December 2025 that a two-year cooling retrofit at its NERSC supercomputing facility cut non-IT power draw, the electricity a data centre spends on cooling rather than compute, by 42%, saving more than 2 million kilowatt-hours a year
Verified 2026-09-27
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- AI data centres worldwide reached a power capacity comparable to New York State at peak demand in 2025, which Stanford's AI Index puts at 29.6 gigawatts
- OpenAI does not disclose GPT-4o's resource footprint, so Stanford's 2026 AI Index Report turned to independent researchers' estimates of the water needed to cool the servers behind it — as much as 1.58 million kilolitres a year — more than 1.2 million people drink annually
- AI training's carbon footprint has scaled by orders of magnitude. Stanford's 2026 AI Index estimates that training AlexNet in 2012 produced about 0.01 tons of CO2 equivalent, while training xAI's Grok 4 in 2025 produced roughly 72,816 tons of CO2 equivalent — over 1,150 times the lifetime emissions of an average car