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Researcher: the "reasoning link" of the AI model consumes more power, and the industry's electricity consumption will be "comparable to that of the Netherlands" in 2027.

2025-04-05 Update From: SLTechnology News&Howtos shulou NAV: SLTechnology News&Howtos > IT Information >

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Shulou(Shulou.com)11/24 Report--

CTOnews.com, October 13 (Xinhua)-- Joule, a sister journal of Cell, published a paper entitled "growing artificial Intelligence Energy footprint (The growing energy footprint of artificial intelligence)" this week.

According to CTOnews.com, the paper, published by Alex De Vries, founder of Digiconomist, claims that the reasoning performance of AI may consume a lot of electricity in the future, and that by 2027, AI may consume as much electricity as one year in the Netherlands.

Alex De Vries says it has always been believed that training an AI model is "the most power-consuming phase of AI", but Vries cited reports from SemiAnalysis and Google that "inference" consumes more power, with 60 per cent of AI-related energy consumption expected to come from model inferences from 2019 to 2021.

Alex De Vries, a paper related to ▲ sources, also calculated based on the 18.3 TWh power consumption disclosed by Google in 2021, claiming that AI accounted for 10% of Google's overall power consumption at that time, and that after Google fully implemented "AI search", the company's AI power consumption could reach 27.4 TWh, close to the electricity used in Ireland for the whole year (29.3 TWh).

In terms of the market as a whole, with the new CoWoS plant invested by Nvidia partner TSMC (TSMC) expected to produce capacity in 2027, Alex De Vries also estimates that the total power consumption of all AI servers delivered by Nvidia will reach 85-134 TWh, equivalent to one year's electricity use in the Netherlands.

Alex De Vries believes that the AI industry should improve the hardware efficiency and model calculus efficiency in order to improve the power consumption of the industry. He also suggests that developers should not only focus on optimizing AI, but also consider the necessity of using AI to reduce the energy consumption cost of the AI industry.

Referenc

The growing energy footprint of artificial intelligence

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