Google apologizes for ‘missing the mark’ after Gemini generated racially diverse Nazis::Google says it’s aware of historically inaccurate results for its Gemini AI image generator, following criticism that it depicted historically white groups as people of color.

  • sxt@lemmy.world
    link
    fedilink
    English
    arrow-up
    16
    ·
    9 months ago

    Part of the problem with talking about these things in a casual setting is that nobody is using precise enough terminology to approach the issue so others can actually parse specifically what they’re trying to say.

    Personally, saying the AI “knows” something implies a level of cognizance which I don’t think it possesses. LLMs “know” things the way an excel sheet can.

    Obviously, if we’re instead saying the AI “knows” things due to it being able to frequently produce factual information when prompted, then yeah it knows a lot of stuff.

    I always have the same feeling when people try to talk about aphantasia or having/not having an internal monologue.

    • barsoap@lemm.ee
      link
      fedilink
      English
      arrow-up
      2
      arrow-down
      3
      ·
      edit-2
      9 months ago

      Personally, saying the AI “knows” something implies a level of cognizance which I don’t think it possesses. LLMs “know” things the way an excel sheet can.

      Yes and the Excel sheet knows. There’s been some stick up your ass CS folks in the past railing about “computers don’t know things, sorting algorithms don’t understand how to sort”, they’ve long since given up. They claimed that saying such things is representative of a bad understanding of how things work yet people casually employing that kind of language often code circles around people who don’t, fact of the matter is many people’s minds like to think of actor forces as animated. “If the light bridge is tripped the machine knows you’re there and stops because we taught it not to decapitate you”.

    • FooBarrington@lemmy.world
      link
      fedilink
      English
      arrow-up
      7
      arrow-down
      12
      ·
      9 months ago

      I can ask AI models specific questions about knowledge it has, which it can correctly reply to. Excel sheets can’t do that.

      That’s not to say the knowledge is perfect - but we know that AI models contain partial world models. How do you differentiate that from “cognizance”?

      • rambaroo@lemmy.world
        link
        fedilink
        English
        arrow-up
        14
        arrow-down
        6
        ·
        edit-2
        9 months ago

        Omg give me a break with this complete nonsense. LLMs are not an intelligence. They are language processors. They do not “think” about anything and don’t have any level of self awareness that implies cognizance. A cognizant ai would have recognized that the Nazis it was creating looked historically inaccurate, based on its training data. But guess what, it didn’t do that because it’s fundamentally incapable of thinking about anything.

        So sick of reading this amateurish bullshit on social media.

        • EatATaco@lemm.ee
          link
          fedilink
          English
          arrow-up
          4
          arrow-down
          2
          ·
          9 months ago

          This gets the question…how do we think? Are we not just language (and other inputs as well) processors? I’m not sure the answer is “no.”

          I also listened to an interesting podcast, I believe it was this American life or some other npr one, about whether ai has intelligence. To avoid the just “compressed knowledge” they came up with questions that the ai almost certainly would not have found in the web. Early ai models were clearly just predicting the next word, and the example was asking it to stack a list of objects. And it just said to stack them one on top of another, in a way that would no way be stable.

          However when they asked a new model to do the same, with the stipulation that it explain it’s reasoning, it stacked the objects in a way that would likely be stable. Even noting that the nail on top should be placed on the head so it doesn’t roll around, and laying eggs down in a grid between a book and a plank of wood so they wouldn’t roll out.

          Another experiment they did was take a language model and asked it to use some obscure programming language to draw a picture of a unicorn. Now this is a language model, not trained on any images.

          And you know what it did? It produced a picture of a unicorn. Just in rough shapes, but even when they moved the horn and flipped it around, it was able to put it back. Without even ever seeing a unicorn, or anything even, it was able to draw a picture of one.

          I don’t think the answer is as simple and clear as you want it to be. And the fact that it “fucked up” on a vague prompt doesn’t really prove anything. Even humans do stupid shit like this if they learn something incorrectly.

        • FooBarrington@lemmy.world
          link
          fedilink
          English
          arrow-up
          4
          arrow-down
          9
          ·
          9 months ago

          A cognizant ai would have recognized that the Nazis it was creating looked historically inaccurate, based on its training data.

          Do you understand that the model is specifically prompted to create “historically inaccurate looking Nazis”? Models aren’t supposed to inject their own guidelines and rules, they simply produce output for your input. If you tell it to produce black Hitler it will produce a black Hitler. Do you expect the model to instead produce white Hitler?