Why I Resist Generative “AI” – Esther Weidauer
estherweidauer.com
Everything, from the ecological to the psychological to the weird
  • Slashme@lemmy.world
    15·
    5 hours ago

    “AI” is certainly environmentally damaging and dangerous, and if it isn’t given new input, it quickly starts generating absolute crap, but I don’t agree with this statement:

    LLMs are simply not capable of producing new knowledge. They can only reproduce what’s in their training data. An LLM-based system, being a statistical model of its training data and therefore effectively a form of lossy compression, can by definition never solve any problem for which the training data or information otherwise available to the system doesn’t already contain the solution.

    We’ve seen new mathematical proofs coming out of LLMs. Those proofs weren’t in the dataset that they were trained on.

    AlphaGo Zero was given the rules of go and made to play against itself with no example games. It came up with new openings that hadn’t been seen before, and were better than anything that humans had come up with.

    AlphaFold was given protein sequences and was able to generate correct 3D structures, that again weren’t in its training data.

    Trying to defend the position of “nothing new comes out of AI” will necessarily lead you to such a narrow definition of novelty, that it will exclude most things that we consider to be human creativity.

    • crunchpaste@lemmy.dbzer0.comEnglish
      71·
      3 hours ago

      Neither AlphaGo, not AlphaFold are LLMs though.

      Also the mathematical proofs you’re talking about seem to be mostly stolen by OpenAI from scientists that interacted with their chatbot before publishing their research.

    • jaredwhite@piefed.socialEnglish
      51·
      5 hours ago

      Computers have “come up with” solutions to problems that eluded human-only problem-solving for decades. That’s literally what computers are supposed to be for. That proves nothing about the novelty of AI beyond a narrow range of incremental problem-based solving which, again, we’ve used computers for for decades.