A.I.’s un-learning problem: Researchers say it’s virtually impossible to make an A.I. model ‘forget’ the things it learns from private user data - eviltoast
As it turns out, it’s impossible to remove a user’s data from a trained A.I. model. Deleting the model entirely is also difficult—and there’s little regulation to enforce either option.

I’m rather curious to see how the EU’s privacy laws are going to handle this.

(Original article is from Fortune, but Yahoo Finance doesn’t have a paywall)

  • Veraticus@lib.lgbtEnglish
    16·
    1 year ago

    You can indeed tell if something is true or untrue. You might be wrong, but that is quite different – you can have internal knowledge that is right or wrong. The very word “misremembered” implies that you did (or even could) know it properly.

    LLMs do not retain facts and they can and frequently do get information wrong.

    Here’s a good test. Choose a video game or TV show you know really well – something a little older and somewhat complicated. Ask ChatGPT about specific plot points in the video game.

    As an example, I know Final Fantasy 14 extremely well and have played it a long time. ChatGPT will confidently state facts about the game that are entirely and totally incorrect: it confuses characters, it moves plot points around. This is because it chooses what is likely to say, not what is actually correct. Indeed, it has no ability to know what is correct at all.

    AI is not a simulation of human neural networks. It uses the concept of mathematical neural networks, but it is a word model, nothing more.

    • fsmacolyte@lemmy.worldEnglish
      2·
      1 year ago

      The free version gets things wrong a bunch. It’s impressive how good GPT-4 is. Human brains are still a million times better in almost every way (they cost a few dollars of energy to operate per day, for example) but it’s really hard to believe how capable the state of the art of LLMs is until you’ve tried it.

      You’re right about one thing though. Humans are able to know things, and to know when we don’t know things. Current LLMs (transformer-based architecture) simply can’t do that yet.