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

  • @[email protected]English
    8•1 month ago

    I’ve run an LLM on my desktop GPU and gotten decent results, albeit not nearly as good as what ChatGPT will get you.

    Probably used less than 0.1Wh per response.

    • @MonsieurmoucheEnglish
      1•1 month ago

      Is this for inferencing only? Do you include training?

      • @[email protected]English
        2•1 month ago

        Inference only. I’m looking into doing some fine tuning. Training from scratch is another story.

      • @[email protected]English
        2•1 month ago

        Training is a one time thing. Tge more it get use, the less energy per query it will take

        • @MonsieurmoucheEnglish
          1•30 days ago

          Good point. But considering the frequent retraining, the environmental impacts can only be spread on a finite number of queries.

          • @[email protected]English
            1•30 days ago

            They have already reached diminishing returns on training. It will become much less frequent soon. Retraining on the same data if there isn’t a better method is useless. I think the ressources consumed per query should only include those actually used for inference. The rest can be dismissed as bad faith argumentation.