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Joined 2 years ago
Cake day: October 9th, 2023
  • GiveMemes@jlai.lutoTechnology@lemmy.world•Admit it: ‘Artificial general intelligence’ may already be obsolete, Expecting OpenAI’s GPT and other large language models to beat humans at thinking like a human might be missing the point.English
    1·
    1 year ago

    The legal system has nothing to do with understanding and everything to do with arbitrarily assigned human bullshit (just like the turing test). While law tends to be rational, it’s notoriously shit as a way of understanding the universe. (Live in a fascist country? Well, the law’s the law). I really regret trying to use that quote as an example because you’ve ratcheted onto it like a bulldog and simply can’t let go.

    Science is the only way by which we can advance our understanding of the universe. There are cases of unknowable questions in which people use philosophy or religion to try and fill the gap, but they still never actually know, just think.

    That wasn’t the exact study I was referencing, but it is actually better at explaining some of the related concepts both in analogy and in their discussion (a discussion in which, they admit that what they think their findings indicate and what their findings actually indicate could be two different things.)

    But, to conclude that somehow the multidimensional set of vectors is mapping the board out because when you change part of the input data, even counterfactual input data in which the computer hasn’t seen that move before as it’s illegal, the output data changes is another huge leap. Of course the data changes, as the patterns change, and the gpt has internalized the patterns in its training data, just as it internalizes syntax and rules of language.

    I don’t think that it really has any meaningful impact if they were incorrect, but if they are correct it could mean that AI is somehow creating a representation of data within itself, which really also wouldn’t surprise me.

    I guess I was more arguing against the guy trying to quote the study at me in the first place than the study itself, though I do have my issues with their analogy bc it’s simply clownish to compare a crow to a mathematical construct purposely created to internalize the rules and syntax of language.

    Also that journal has a high schooler on the board of editorialists and has no name for itself… not exactly The Journal of Machine Learning Research lol

  • GiveMemes@jlai.lutoTechnology@lemmy.world•Admit it: ‘Artificial general intelligence’ may already be obsolete, Expecting OpenAI’s GPT and other large language models to beat humans at thinking like a human might be missing the point.English
    1·
    1 year ago

    Isn’t this basically just what my comment about the edge of the knowable was and you snarkily replied with the Turing Test?

    Like go watch one of the videos I linked if you haven’t. I think they’d be really interesting to you, especially the first one.

    I agree with you tho. What are we looking for is the question to ask. By that same notion, I can say with certainty for myself that what we have doesn’t reason, but I can’t elaborate on what it might take to make up something that does. Just as with obscenity in that famous SC case.

    To elaborate on the Othello point:

    They tested the LLM with a probe and changed a board piece. They used this change and probed the resultant probability distribution to determine whether or not the AI would change its probability distribution to ‘prove’ that it was creating world representations of the board. The problem is, and this is what makes it kinda fallacious thinking by the study authors, that if you change the input data of course the output data is going to change. That’s just a result of training the AI on different legal boardstates, as the way that moves that are made will have a direct result on the placement of the pieces.

    Furthermore, they showed that it outperformed random chance at predicting legal moves, but that’s just the way that training AI works. An LLM is better at predicting the next word than random chance as a result of its training.

    If you don’t really get what I’m talking about here I recommend this video: https://m.youtube.com/watch?v=wjZofJX0v4M&vl=en

  • GiveMemes@jlai.lutoTechnology@lemmy.world•Admit it: ‘Artificial general intelligence’ may already be obsolete, Expecting OpenAI’s GPT and other large language models to beat humans at thinking like a human might be missing the point.English
    1·
    1 year ago

    I really just don’t get why somebody would get emotional over an argument like this but to each their own I suppose. The reason for the emotionality of my reply is rather simply stated: I still don’t believe you had any intent to spare anybody ‘emotional distress’ and were trying to remain aloof and, honestly, rather cunty, by bringing up something literally everybody even mildly interested in AI knows all about as if it’s the end all be all of understanding the potential of thinking arising from a machine. On top of that, you purposefully haven’t engaged with any of the points directly refuting the things you’ve said. Honestly, some of the emotionality comes from when I remember being like you, thinking I knew everything, and whenever somebody would hold me to my words I’d do something along the lines of what you’re doing (engaging in argumentative discussion dishonestly in order to maintain the appearance of ‘winning’ when I really should have been learning more and changing my mind instead of bringing up the same tired pop-culture “smart people” bs.)

    Anyway,

    My point wasn’t about obscenity. It’s about the nebulousness of something like reason, and the Turing test isn’t scientific in the first place, so I’m really not sure where you got all this ‘science vs law’ bs from.

    The point wasn’t that reason is like obscenity, but that I can clearly see, from the way that we train LLMs, that they aren’t reasoning in any form, rather using values that have been derived over time from the training data fed in and the ‘reward’ system used to get the right answers over time. An LLM is no more than a complicated calculator, controlled in many ways by the humans that train it, just as with any form of machine learning. Rather that I “know it when I see it”

    I’ve read some studies on ‘game states’ which is the closest that ai scientists have come to anything resembling reason, but even in a model that played the relatively simple game of Othello, the metric they were testing the AI (which was trained on data of legal Othello boardstates) against to ‘prove’ that it was ‘thinking’ (creating game states) was that it was doing better at choosing legal moves than random chance. Another reason it might have been doing better than random chance? Oh yeah… the training data full of legal boardstates. And when the AI was trained on less data? Oh? Would you look at that? The margin by which it beats random chance falls drastically. Almost like the LLM has no fucking clue what’s going on and it’s just matching boardstates… indexing. It doesn’t understand the rules of Othello; it’s just matching piece placement locations with the legal boardstates it was trained on. A human trained on even a few hundred (vs thousands) of such boardstates could likely start to reason out the rules of the game quite easily.

    I’m not even against AI or anything, but to call the machine learning that we have now anything close to true, thinking AI is just foolish talk.

  • GiveMemes@jlai.lutoTechnology@lemmy.world•Admit it: ‘Artificial general intelligence’ may already be obsolete, Expecting OpenAI’s GPT and other large language models to beat humans at thinking like a human might be missing the point.English
    1·
    1 year ago

    That’s kinda the whole point of my comment is that things like Turing’s method completely fall apart under heavy scrutiny. Further, the Turing Test specifically tells you nothing about whether or not something IS thinking, just that it MAY be. Big difference.

    I see you didn’t engage with the rest of my comment tho. Would you like to?

    Just wanted to add this as it and stuff like it comes up pretty quickly when you research the turing test:

    "On the other hand, there are several criticisms and limitations of the Turing Test as a measure of machine intelligence. Some of the main issues include:

    The test focuses solely on the ability to mimic human-like behavior and communication, rather than on the underlying intelligence or consciousness of the machine.

    The test is heavily dependent on the human evaluator’s subjective judgment, and may be influenced by factors such as the machine’s appearance or the human’s own biases.

    The test does not take into account the possibility that a machine could be intelligent in ways that are fundamentally different from human intelligence.

    The test does not consider the possibility of a machine deceiving the human evaluator, by providing pre-programmed or rehearsed responses rather than truly understanding the meaning of the questions."

    LLMs would fall into the last, as they train on the “answers” so to speak and just match them to the “question”.