this post was submitted on 21 Aug 2025
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[–] finitebanjo@piefed.world 7 points 5 days ago* (last edited 5 days ago) (1 children)

Because the training has diminishing returns, meaning the small improvements between (for example purposes) GPT 3 and 4 will need exponentially more power to have the same effect on GPT 5. In 2022 and 2023 OpenAI and DeepMind both predicted that reaching human accuracy could never be done, the latter concluding even with infinite power.

So in order to get as close as possible then in the future they will need to get as much power as possible. Academic papers outline it as the one true bottleneck.

[–] Valmond@lemmy.world 1 points 4 days ago (1 children)

And academia will work on that problem. It reminds me of intel processors "projected" to use kilowatts of energy, then smart people made other types of chips and they don't need 2000 watts.

[–] finitebanjo@piefed.world 1 points 3 days ago* (last edited 3 days ago) (1 children)

Academia literally got cut by more than a third and Microsoft is planning to revive breeder reactors.

You might think academia will work on the problem but the people running these things absolutely do not.

[–] Valmond@lemmy.world -1 points 3 days ago (1 children)
[–] finitebanjo@piefed.world -2 points 2 days ago

Did the EU suddenly develop a tech industry overnight or are you unaware where all the major AI companies are located?