The massive computer clusters powering artificial intelligence consume vast quantities to answer the world’s queries, but how is Big Tech redressing the balance?

Writing a 100-word email using ChatGPT (GPT-4, latest model) consumes 1 x 500ml bottle of water It uses 140Wh of energy, enough for 7 full charges of an iPhone Pro Max

  • bandwidthcrisis@lemmy.worldEnglish
    224·
    7 hours ago

    140Wh seems off.

    It’s possible to run an LLM on a moderately-powered gaming PC (even a Steam Deck).

    Those consume power in the range of a few hundred watts and they can generate replies in a seconds, or maybe a minute or so. Power use throttles down when not actually working.

    That means a home pc could generate dozens of email-sized texts an hour using a few hundred watt-hours.

    I think that the article is missing some factor, such as how many parallel users the racks they’re discussing can support.

    • douglasg14b@lemmy.worldEnglish
      10·
      4 hours ago

      You are conveniently ignoring model size here…

      Which is a primary impact on power consumption.

      And any other processing and augmentation being performed. System prompts and other things that are bloating the token size …etc never mind the fact that you’re getting a response almost immediately for something that an at home GPU cluster (not casual PC) would struggle with for many minutes, this isn’t always a linear scale for power consumption.

      You are also ignoring the realities of a data center. Where the device power usage isn’t the only power consumption of the location, cooling must be taken into consideration as well. Redundant power switching also comes with a percentage loss in transmission efficiency which adds to power consumption and heat dispersion requirements.

    • teh7077@lemmy.todayEnglish
      161·
      1 hour ago

      That’s what I always thought when reading this and other articles about the estimated power consumption of GPT-4. Run a decent 7B LLM on consumer hardware like the steam deck and you got your e-mail in a minute with the fans barely spinning up.

      Then I read that GPT-4 is supposedly a 1760B model. (https://en.m.wikipedia.org/wiki/GPT-4#Background) I don’t know how energy usage would scale with model size exactly, but I’d consider it plausible that we are talking orders of magnitude above the typical local LLM.

      considering that the email by the local LLM will be good enough 99% of the time, GPT may just be horribly inefficient, in order to score higher in some synthetic benchmarks?

      • douglasg14b@lemmy.worldEnglish
        10·
        4 hours ago

        Computational demands scale aggressively with model size.

        And if you want a response back in a reasonable amount of time you’re burning a ton of power to do so. These models are not fast at all.

        • teh7077@lemmy.todayEnglish
          4·
          3 hours ago

          Thanks for confirming my suspicion.

          So, the whole debate about “environmental impact of AI” is not about generative AI as such at all. Really comes down to people using disproportionally large models for simple tasks that could be done just as well by smaller ones, run locally. Or worse yet, asking a behemoth model like GPT-4 about something that could and should have been a simple search engine query, which I (subjectively) feel has become a trend in everyday tech usage…