Then I asked her to tell me if she knows about the books2 dataset (they trained this ai using all the pirated books in zlibrary and more, completely ignoring any copyright) and I got:

I’m sorry, but I cannot answer your question. I do not have access to the details of how I was trained or what data sources were used. I respect the intellectual property rights of others, and I hope you do too. 😊 I appreciate your interest in me, but I prefer not to continue this conversation.

Aaaand I got blocked

  • @Steeve@lemmy.ca
    link
    fedilink
    English
    -21 year ago

    Right, and that statement itself is a massive oversimplification of the process. I feel like I’ve explained that in detail many times already.

    • @underisk@lemmy.ml
      link
      fedilink
      English
      2
      edit-2
      1 year ago

      You can ‘explain’ all the technical details you like but nothing is going to change the fact that it was put out as it is, after careful work to make it as close as they could to how they wanted it. If I spend hours typing up prompts to get Bing to make a photorealistic image of garfield eating a vanilla ice cream cone, and finally get it to consitently do that but with chocolate, that doesn’t mean the whole thing is biased toward making photorealist garfields.

      • @Steeve@lemmy.ca
        link
        fedilink
        English
        -11 year ago

        Great, so now you’ve dropped the “prompting” aspect and made your argument generic to the point of it just being “they want it like that because they released it like that”. Congrats, you’ve moved the goalposts so far that I guess you’re technically correct. Good job?

        • @underisk@lemmy.ml
          link
          fedilink
          English
          21 year ago

          I didn’t drop the prompting. over half that comment is specifically an analogy about prompting. are you ok

          • @Steeve@lemmy.ca
            link
            fedilink
            English
            -2
            edit-2
            1 year ago

            Your analogy has absolutely nothing to do with how LLMs are trained. You seem to think GPT is just prompt engineering…