Comment on We hate AI because it's everything we hate

• iopq@lemmy.world ⁨1⁩ ⁨week⁩ ago

  Servers have been eating up a significant portion of electricity for years before AI. It’s whether we get something useful out of it that matters

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  • Deflated0ne@lemmy.world ⁨1⁩ ⁨week⁩ ago

    That’s the hangup isn’t it? It produces nothing of value. Stolen art. Bad code. Even more frustrating phone experiences. Oh and millions of lost jobs and ruined lives.

    It’s the most american way possible that they could have set trillions of dollars on fire short of carpet bombing poor brown people somewhere.

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  • CorvidCawder@sh.itjust.works ⁨1⁩ ⁨week⁩ ago

    Not even remotely close to this scale… At most you could compare the energy usage to the miners in the crypto craze, but I’m pretty sure that even that is just a tiny fraction of what’s going on right now.

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    • Deflated0ne@lemmy.world ⁨1⁩ ⁨week⁩ ago

      Crypto miners wish they could be this inefficient. No literally they do. They’re the “rolling coal” mfers of the internet.

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    • iopq@lemmy.world ⁨6⁩ ⁨days⁩ ago

      Very wrong

      In 2023 AI used 40 TWh of energy in the US out of a total 176 TWh used by data centers

      davidmytton.blog/how-much-energy-do-data-centers-…

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      • CorvidCawder@sh.itjust.works ⁨6⁩ ⁨days⁩ ago

        From the blog you quoted yourself:

        Despite improving AI energy efficiency, total energy consumption is likely to increase because of the massive increase in usage. A large portion of the increase in energy consumption between 2024 to 2023 is attributed to AI-related servers. Their usage grew from 2 TWh in 2017 to 40 TWh in 2023. This is a big driver behind the projected scenarios for total US energy consumption, ranging from 325 to 580 TWh (6.7% to 12% of total electricity consumption) in the US by 2028.

        (And likewise, the last graph of predictions for 2028)

        From a quick read of that source, it is unclear to me if it factors in the electricity cost of training the models. It seems to me that it doesn’t.

        I found more information here: technologyreview.com/…/ai-energy-usage-climate-fo…

        Racks of servers hum along for months, ingesting training data, crunching numbers, and performing computations. This is a time-consuming and expensive process—it’s estimated that training OpenAI’s GPT-4 took over $100 million and consumed 50 gigawatt-hours of energy, enough to power San Francisco for three days.

        So, I’m not sure if those numbers for 2023 paint the full picture. And adoption of AI-powered tools was definitely not as high in 2023 as it is nowadays. So I wouldn’t be surprised if those numbers were much higher than the reported 22.7% of the total server power usage in the US.

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• jj4211@lemmy.world ⁨6⁩ ⁨days⁩ ago

  It probably would have if IBM decided that every household in the USA needed to have chess playing compute capacity and made everyone dial up to a singular facility in the middle of a desert where land and taxes were cheap so they could charge everyone a monthly fee for the privilege…

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