For the record this is alarmist bs. The article literally concedes that the power needs of AI haven’t been growing at a rapid rate (like crypto mining did).

Besides, advances in analog methods of computing specifically for the matrix multiplication that makes up the bulk of computing power needed are something like 15-60x more efficient while operating at a lower overall speed. When used together however, these analog chips can produce just as much computational power as digital chips at a fraction of the energy consumption. The chips are only really useful for training AI though, as they’re specifically engineered for matrix multiplication, so don’t expect analog computing to come back in other areas

This is the best summary I could come up with:

The new analysis was written by Alex de Vries, a researcher who has called attention to pollution stemming from crypto mining with his website Digiconomist.

Last week, Google even showed off new AI-powered tools for policymakers to cut down tailpipe emissions and prepare communities for climate change-related disasters like floods and wildfires.

But if we look historically at research and also our own experience, it’s that AI compute demand has gone up much more slowly than the power needed for it,” Google chief sustainability officer Kate Brandt said in a press briefing last week.

“The energy needed to power this technology is increasing at a much slower rate than many forecasts have predicted,” Corina Standiford, a spokesperson for Google, said in an email.

The paper includes a little more realistic scenario calculating the potential energy consumption of the 100,000 AI servers Nvidia is expected to deliver this year.

Even so, that electricity use could grow sharply if AI’s popularity continues to skyrocket and supply chain constraints loosen, de Vries writes.

The original article contains 645 words, the summary contains 168 words. Saved 74%. I’m a bot and I’m open source!