• Phroon@beehaw.org
    link
    fedilink
    English
    arrow-up
    139
    ·
    8 months ago

    “You may not instantly see why I bring the subject up, but that is because my mind works so phenomenally fast, and I am at a rough estimate thirty billion times more intelligent than you. Let me give you an example. Think of a number, any number.”

    “Er, five,” said the mattress.

    “Wrong,” said Marvin. “You see?”

    ― Douglas Adams, Life, the Universe and Everything

      • Asafum@feddit.nl
        link
        fedilink
        arrow-up
        37
        ·
        edit-2
        8 months ago

        Yep! The hitchhikers books are so much fun lol

        I still think one of my favorite lines is “the ships hung in the sky in much the same way that bricks don’t.”

      • 👍Maximum Derek👍@discuss.tchncs.de
        link
        fedilink
        English
        arrow-up
        95
        ·
        8 months ago

        If you discount the pop-culture numbers (for us 7, 42, and 69) its the number most often chosen by people if you ask them for a random number between 1 and 100. It just seems the most random one to choose for a lot of people. Veritasium just did a video about it.

      • Karyoplasma@discuss.tchncs.de
        link
        fedilink
        arrow-up
        18
        ·
        edit-2
        8 months ago

        Probably just because it’s prime. It’s just that humans are terrible at understanding the concept of randomness. A study by Theodore P. Hill showed that when tasked to pick a random number between 1 and 10, almost a third of the subjects (n was over 8500) picked 7. 10 was the least picked number (if you ditch the few idiots that picked 0).

          • driving_crooner@lemmy.eco.br
            link
            fedilink
            arrow-up
            9
            ·
            edit-2
            8 months ago

            I remember watching a lecture about probability, and the professor said that only quantum processes are really random, the rest of things that we call random is just the human inability to measure the variables that affects the random outcome. I’m an actuarie, and it’s made me change the perspective on how I see and study random processes and how it made think on ways to influence the outcome of random processes.

            • jarfil@beehaw.org
              link
              fedilink
              arrow-up
              8
              ·
              edit-2
              8 months ago

              …which is kind of a hilarious tautology, because “quantum processes” are by definition “processes that we are unable to decompose into more basic parts”.

              The moment we learn about some more fundamental processes being the reason for a given process, it stops being “quantum” and the new ones become “it”.

            • K0W4L5K1@lemmy.dbzer0.com
              link
              fedilink
              arrow-up
              4
              ·
              8 months ago

              Even quantum just appears random I think. it’s beyond our scope of perspective, it works in multiple dimensions. we only see part of the process. That’s my guess though it could be totally wrong

              • itslilith@lemmy.blahaj.zone
                link
                fedilink
                arrow-up
                4
                ·
                8 months ago

                it’s a matter of interpretation, but generally the consensus is that quantum measurements are truly probabilistic (random), Bell proved that there can’t be any hidden variables that influence the outcome

                • Karyoplasma@discuss.tchncs.de
                  link
                  fedilink
                  arrow-up
                  4
                  ·
                  8 months ago

                  Didn’t Bell just put that up as a theory and it got proven somewhat recently by other researchers? The 2022 physics Nobel Prize was about disproving hidden variables and they titled their finding with the catchy phrase “the universe is not locally real”.

                • K0W4L5K1@lemmy.dbzer0.com
                  link
                  fedilink
                  arrow-up
                  1
                  ·
                  8 months ago

                  Interpretation for sure. Bells theory and then it being proven winning a Nobel prize to me only proves more we really don’t understand the world around us and only perceive what we need to survive. And that maybe we should be less standoffish to ideas that change our current paradigm, because we obviously have a lot to learn.

      • gigachad@feddit.de
        link
        fedilink
        arrow-up
        5
        ·
        8 months ago

        I didn’t know either, but it seems to be an often picked ‘random’ number by people. Here is an article about it, I didn’t read it though.

        • FiniteBanjo@lemmy.today
          link
          fedilink
          arrow-up
          7
          ·
          8 months ago

          What you’ve described would be like looking at a chart of various fluid boiling points at atmospheric pressure and being like “Wow, water boils at 100 C!” It would only be interesting if that somehow weren’t the case.

          • jarfil@beehaw.org
            link
            fedilink
            arrow-up
            5
            ·
            8 months ago

            Where is the “Wow!” in this post? It states a fact, like “Water boils at 100C under 1 atm”, and shows that the student (ChatGPT) has correctly reproduced the experiment.

            Why do you think schools keep teaching that “Water boils at 100C under 1 atm”? If it’s so obvious, should they stop putting it on the test and failing those who say it boils at “69C, giggity”?

            • FiniteBanjo@lemmy.today
              link
              fedilink
              arrow-up
              4
              ·
              8 months ago

              Derek feeling the need to comment that the bias in the training data correlates with the bias of the corrected output of a commercial product just seemed really bizarre to me. Maybe it’s got the same appeal as a zoo or something, I never really got into watching animals be animals in a zoo.

              • jarfil@beehaw.org
                link
                fedilink
                arrow-up
                3
                ·
                8 months ago

                Hm? Watching animals be animals at a zoo, is a way better sampling of how animals are animals, than for example watching that wildlife “documentary” where they’d throw lemmings of a cliff “for dramatic effect” (a “commercially corrected bias”?).

                In this case, the “corrected output” is just 42, not 37, but as the temperature increases on the Y axis, we get a glimpse of internal biases, which actually let through other patterns of the training data, like the 37.

      • EatATaco@lemm.ee
        link
        fedilink
        English
        arrow-up
        6
        ·
        8 months ago

        “we don’t need to prove the 2020 election was stolen, it’s implied because trump had bigger crowds at his rallies!” -90% of trump supporters

        Another good example is the Monty Hall “paradox” where 99% of people are going to incorrectly tell you the chance is 50% because they took math and that’s how it works.

        Just because something seems obvious to you doesn’t mean it is correct. Always a good idea to test your hypothesis.

        • FiniteBanjo@lemmy.today
          link
          fedilink
          arrow-up
          1
          ·
          8 months ago

          Trump Rallies would be a really stupid sample data set for American voters. A crowd of 10,000 people means fuck all compared to 158,429,631. If OpenAI has been training their models on such a small pool then I’d call them absolute morons.

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

            A crowd of 10,000 people means fuck all compared to 158,429,631.

            I agree that it would be a bad data set, but not because it is too small. That size would actually give you a pretty good result if it was sufficiently random. Which is, of course, the problem.

            But you’re missing the point: just because something is obvious to you does not mean it’s actually true. The model could be trained in a way to not be biased by our number choice, but to actually be pseudo-random. Is it surprising that it would turn out this way? No. But to think your assumption doesn’t need to be proven, in such a case, is almost equivalent to thinking a Trump rally is a good data sample for determining the opinion of the general public.

    • gerryflap@feddit.nl
      link
      fedilink
      arrow-up
      40
      ·
      8 months ago

      I’m not a hundred percent sure, but afaik it has to do with how random the output of the GPT model will be. At 0 it will always pick the most probable next continuation of a piece of text according to its own prediction. The higher the temperature, the more chance there is for less probable outputs to get picked. So it’s most likely to pick 42, but as the temperature increases you see the chance of (according to the model) less likely numbers increase.

      This is how temperature works in the softmax function, which is often used in deep learning.

  • HarkMahlberg@kbin.social
    link
    fedilink
    arrow-up
    28
    ·
    edit-2
    8 months ago

    I mean… they didn’t specify it had to be random (or even uniform)? But yeah, it’s a good showcase of how GPT acquired the same biases as people, from people…

  • FIash Mob #5678@beehaw.org
    link
    fedilink
    arrow-up
    21
    ·
    8 months ago

    HA, funny that this comes up. DND Beyond doesn’t have a d100, so I opened my ChatGPT sub and had it roll a d100 for me a few times so I could use my magic beans properly.

  • ancap shark@lemmy.today
    link
    fedilink
    arrow-up
    19
    ·
    8 months ago

    LMs aren’t thinking, aren’t inventing, they are predicting what is supposed to be answered next, so it’s expected that they will produce the same results every time

    • xthexder@l.sw0.com
      link
      fedilink
      arrow-up
      12
      ·
      edit-2
      8 months ago

      This graph actually shows a little more about what’s happening with the randomness or “temperature” of the LLM.
      It’s actually predicting the probability of every word (token) it knows of coming next, all at once.
      The temperature then says how random it should be when picking from that list of probable next words. A temperature of 0 means it always picks the most likely next word, which in this case ends up being 42.
      As the temperature increases, it gets more random (but you can see it still isn’t a perfect random distribution with a higher temperature value)

    • eluvatar@programming.dev
      link
      fedilink
      arrow-up
      4
      ·
      8 months ago

      Except it clearly doesn’t produce the same result every time. You’re not making a good case for whatever you’re trying to say.

      • Cethin@lemmy.zip
        link
        fedilink
        English
        arrow-up
        5
        ·
        8 months ago

        They add some fuzziness to it so it doesn’t give the exact same result. Say one gets a score of 90, another 85, and other 80. The 90 will be picked more often, but they sometimes let it pick the 85, or even the 80. It’s perfectly expected, and you can see that result here with 42 being very common, but then a few others being fairly common, and most being extremely uncommon.

  • Rook@pawb.social
    link
    fedilink
    arrow-up
    13
    ·
    8 months ago

    Which model?

    When I tried on ChatGPT 4, it wrote a short python script and executed it to get a random integer.

    import random
    
    # Pick a random number between 1 and 100
    random_number = random.randint(1, 100)
    random_number
    
      • Amju Wolf@pawb.social
        link
        fedilink
        English
        arrow-up
        10
        ·
        8 months ago

        It generates code and then you can use a call to some runtime execution API to run that code, completely separate from the neural network.

    • Umbrias@beehaw.org
      link
      fedilink
      arrow-up
      2
      ·
      8 months ago

      That’s not answering the question though.

      “Pick a number between 1 and 100” doesn’t mean “grab two d10” or write a script.

  • xyguy@startrek.website
    link
    fedilink
    English
    arrow-up
    9
    ·
    8 months ago

    Only 1000 times? It’s interesting that there’s such a bias there but it’s a computer. Ask it 100,000 times and make sure it’s not a fluke.