[0] https://www.wsj.com/tech/ai/microsoft-targets-nuclear-to-pow...
If you take the "350,000" H100s that Facebook wants by EOY, each of those can do 700W, which gives you almost 250 MW for just the GPUs. That sounds like a lot, until you realize that a single large power plant is measured in Gigawatts. All of Google's data centers combined are O(10 GW) which are matched with renewable power offsets [1].
Importantly, the world installed >500 Gigawatts of renewable energy in 2023 [2], mostly driven by PV Solar in China. The amount of potential solar and wind and other renewable-ish (hydro) outstrips even a 10x'ing of a lot of these numbers. But even for a single site, dams like Three Gorges are >20 GW.
There are real efficiency and scale challenges in doing AI in a single, large site. But existing power generation systems deliver plenty of power.
[1] https://www.gstatic.com/gumdrop/sustainability/google-2023-e...
[2] https://www.iea.org/reports/renewables-2023/executive-summar...
https://www.aboutamazon.com/news/sustainability/amazon-renew...
I want one which can instantly calculate numberwang[0] and get it right every time
> This report also analyzes prospective generation capacity in four categories — under construction, permitted, application pending, and proposed. More than 466,000 MW of new generation capacity is under development in the United States — a 13% increase over 2022. Sixty-one percent of capacity most likely to come online, permitted plants and plants that are under construction, are in solar.
China's growth in power capacity is non-trivially due to increasing demand. If the US or Europe or wherever suddenly wanted to build XXX GW per year, they could (modulo bureaucracy, which is very real).
The US or EU could likely do it, yes. If someone is willing to put up the capital to do it. The point of Sam Altman's statement is that he wants someone to do it.