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We did the math on AI’s energy footprint. Here’s the story you haven’t heard.
(www.technologyreview.com)
this post was submitted on 21 May 2025
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Bold assumption.
Historically AI always got much better. Usually after the field collapsed in an AI winter and several years went by in search for a new technique to then repeat the hype cycle. Tech bros want it to get better without that winter stage though.
AI usually got better when people realized it wasn't going to do all it was hyped up for but was useful for a certain set of tasks.
Then it turned from world-changing hotness to super boring tech your washing machine uses to fine-tune its washing program.
Like the cliché goes: when it works, we don't call it AI anymore.
The smart move is never calling it "AI" in the first place.
Unless you're in comp sci, and AI is a field, not a marketing term. And in that case everyone already knows that's not "it".
The major thing that killed 1960s/70s AI was the Vietnam War. MIT's CSAIL was funded heavily by DARPA. When public opinion turned against Vietnam and Congress started shutting off funding, DARPA wasn't putting money into CSAIL anymore. Congress didn't create an alternative funding path, so the whole thing dried up.
That lab basically created computing as we know it today. It bore fruit, and many companies owe their success to it. There were plenty of promising lines of research still going on.
I wish there was an alternate history forum or novel that explores this scenario.
Pretty sure "AI" didn't exist in the 60s/70s either.
Yes, it did. Most of the basic research came from there. The first section of the book "Hackers" by Steven Levy is a good intro.
The perceptron was created in 1957 and a physical model was built a year later
The spice must flow
Each winter marks the beginning and end of a generation of AI. We are now seeing more progress and as long as there is no technical limit it seems that its progress will not be interrupted.
What progress are we seeing?
NVL72 will be enormously impactful on high end performance.
The issue this time around is infrastructure. The current AI Summer depends on massive datacenters with equally massive electrical needs. If companies can't monetize that enough, they'll pull the plug and none of this will be available to general public anymore.
This system can go backwards. Yes, the R&D will still be there after the AI Winter cycle hits, but none of the infrastructure.
We'll still have models like deepseek, and (hopefully) discount used server hardware
Historically "AI" still doesn't exist.
Technically even 1950s computer chess is classified as AI.