Comment on AI Computing on Pace to Consume More Energy Than India, Arm Says

Rognaut@lemmy.world ⁨1⁩ ⁨month⁩ ago

• kakes@sh.itjust.works ⁨1⁩ ⁨month⁩ ago

  I don’t disagree that they should back up their claim, but it does intuitively make sense. AI - GPT LLMs in particular - are typically designed to push the limits of what modern hardware can provide - essentially eating whatever power you can throw at it.

  Pair this with a huge AI boom and corporate hype cycle, and it wouldn’t surprise me if it was consuming an incredible amount of power. It’s reminiscent of Bitcoin, from a resource perspective.

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  • FaceDeer@fedia.io ⁨1⁩ ⁨month⁩ ago

    No, it makes no sense. India has over a billion people. There's no way that amount of computing power could just magically have poofed into existence over the past few years, nor the power plants necessary to run all of that.

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    • TheOctonaut@mander.xyz ⁨1⁩ ⁨month⁩ ago

      This is a future prediction, not a current observation.

      I’m not saying it’s correct as a prediction, but “where are the extra power plants” is not good counter-argument.

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      • FaceDeer@fedia.io ⁨1⁩ ⁨month⁩ ago

        A couple of months ago the average temperature where I live was well below freezing. Now it's around twenty degrees C.

        By this time next year it'll be thousands of degrees!

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    • BakerBagel@midwest.social ⁨1⁩ ⁨month⁩ ago

      The current LLM’S kinda suck, but companies have fired huge swaths of their staff and plan in putting LLMs in their place. Either those companies hire back all those workers, or they get the programs to not suck. And making LLMs actually capable of working unsupervised will take more and more energy.

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      • kakes@sh.itjust.works ⁨1⁩ ⁨month⁩ ago

        My take is that LLMs are absolutely incredible… for personal use and hobby projects. I can’t think of a single task I would trust an LLM to perform entirely unsupervised in a business context.

        Of course, that’s just where LLMs are at today, though. They’ll improve.

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      • MakePorkGreatAgain@lemmy.basedcount.com ⁨1⁩ ⁨month⁩ ago

        LLM’s will probably improve at an exponential level - similar to how cpu’s did in the 80s/90s. in ~10 generations the LLMs will likely be very useful

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      • FaceDeer@fedia.io ⁨1⁩ ⁨month⁩ ago

        Sure, but it's simply not physically possible for AI to be consuming that much power. Not enough computers exist, and not enough ability to manufacture new ones fast enough. There hasn't been a giant surge of new power plants built in just the past few years, so if something was suddenly drawing an India's worth of power then somewhere an India's worth of consumers just went dark.

        This just isn't plausible.

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    • revv@lemmy.blahaj.zone ⁨1⁩ ⁨month⁩ ago

      If only there had been another widespread, wasteful prior use of expensive and power hungry compute equipment that suddenly became less valuable/effective and could quickly be repurposed to run LLMs…

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      • FaceDeer@fedia.io ⁨1⁩ ⁨month⁩ ago

        Pretty sure the big AI corps aren't depending on obsolete second-hand half-burned-out Ethereum mining rigs for their AI training.

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