Generative AI’s Energy Problem Today is Foundational
Generative AI’s Energy Problem Today is Foundational
Before AI can take over, it will need to find a new approach to energy
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The actual paper (emphasis mine):
In 2021, Google’s total electricity consumption was 18.3 TWh, with AI accounting for 10%–15% of this total.2 The worst-case scenario suggests Google’s AI alone could consume as much electricity as a country such as Ireland (29.3 TWh per year), which is a significant increase compared to its historical AI-related energy consumption. However, this scenario assumes full-scale AI adoption utilizing current hardware and software, which is unlikely to happen rapidly. ... A more pragmatic projection of worldwide AI-related electricity consumption could be derived from NVIDIA’s sales in this segment. Given its estimated 95% market share in 2023, NVIDIA leads the AI servers market. The company is expected to deliver 100,000 of its AI servers in 2023.10 If operating at full capacity (i.e., 6.5 kW for NVIDIA's DGX A100 servers and 10.2 kW for DGX H100 servers), these servers would have a combined power demand of 650–1,020 MW. On an annual basis, these servers could consume up to 5.7–8.9 TWh of electricity. Compared to the historical estimated annual electricity consumption of data centers, which was 205 TWh,2 this is almost negligible.
The article:
de Vries has analyzed trends in AI energy use and predicted that current AI technology could be on track to annually consume as much electricity as the country of Ireland (29.3 terawatt-hours per year.)
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If you want machines to do work, you spend energy. Energy costs money. So if people are spending money to run their machines those machines must be doing work that's worth the cost. I'm not sure what the big surprise is here.
2It would be quite astonishing if all the Climate Change worst-case scenario predictions were to be overshadowed by the energy demands of generative AI over the next decade.
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