As companies race to build AI into their products, there are concerns about the technology’s potential energy use. A new analysis suggests AI could match the energy budgets of entire countries, but the estimates come with some notable caveats.
This uses considerable amounts of energy, for powering the calculations themselves and supporting the massive cooling infrastructure required to keep the chips from melting.
With excitement around generative AI at fever pitch and companies aiming to build the technology into all kinds of products, some are sounding the alarm about what this could mean for future energy consumption.
“Looking at the growing demand for AI service, it’s very likely that energy consumption related to AI will significantly increase in the coming years,” de Vries, who is now a PhD candidate at Vrije Universiteit Amsterdam, said in a press release.
“The potential growth highlights that we need to be very mindful about what we use AI for. It’s energy intensive, so we don’t want to put it in all kinds of things where we don’t actually need it.”
The Google prediction is based on suggestions by the company’s executives that they could build AI into their search engine combined with some fairly rough power consumption estimates from research firm SemiAnalysis.
The analysts at SemiAnalysis suggest that applying AI similar to ChatGPT in each of Google’s nine billion daily searches would take roughly 500,000 of Nvidia’s specialized A100 HGX servers.
Google is unlikely to reach these levels though, de Vries admits, because such rapid adoption is unlikely, the enormous costs would eat into profits, and Nvidia doesn’t have the ability to ship that many AI servers.
Given a similar energy consumption profile, these could be consuming 85 to 134 terawatt-hours a year, he estimates.
They also ignore any potential energy efficiency improvements in either AI models or the hardware used to run them.
While it’s unlikely that AI will be burning through as much power as entire countries anytime soon, its contribution to energy usage and consequent carbon emissions could be significant.