Modern AI data centers consume enormous amounts of power, and it looks like they will get even more power-hungry in the coming years as companies like Google, Microsoft, Meta, and OpenAI strive towards artificial general intelligence (AGI). Oracle has already outlined plans to use nuclear power plants for its 1-gigawatt datacenters. It looks like Microsoft plans to do the same as it just inked a deal to restart a nuclear power plant to feed its data centers, reports Bloomberg.

  • oatscoop@midwest.social
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    1 month ago

    One of the major problems with LLMs is it’s a “boom”. People are rightfully soured on them as a concept because jackasses trying to make money lie about their capabilities and utility – never mind the ethics of obtaining the datasets used to train them.

    They’re absolutely limited, flawed, and there are better solutions for most problems … but beyond the bullshit LLMs are a useful tool for some problems and they’re not going away.

    • finitebanjo@lemmy.world
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      1 month ago

      I cannot think of one single application where an LLM is better or even equivalent than having a person do the job. Its real only use is to trade human workers for cheaper but inferior output, at the detriment to mankind as a whole because we have in excess labor and in shortage power.

      • oatscoop@midwest.social
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        1 month ago

        There are jobs where it’s not feasible or practical to pay an actual human to do.

        Human translators exist and are far superior to machine translators. Do you hire one every time you need something translated in a casual setting, or do you use something Google translate? LLMs are the reason modern machine translation is is infinitely better than it was a few years ago.

        • finitebanjo@lemmy.world
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          1 month ago

          Google Translate was functional BEFORE llms were a hit, arguably moreso, and we had datasets on human language which are now polluted by AI making it harder now to build dictionaries than it was before.