• Phroon@beehaw.org
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    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
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        7 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.”

  • HarkMahlberg@kbin.social
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    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…

    • OsrsNeedsF2P@lemmy.ml
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      8 months ago

      uniform

      Reminds me of my previous job where our LLM was grading things too high. The AI “engineer” adjusted the prompt to tell the LLM that the average output should be 3. I had a hard time explaining that wouldn’t do anything at all, because all the chats were independent events.

      Anyways, I quit that place and the project completely derailed.

  • FIash Mob #5678@beehaw.org
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    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.

    • TauriWarrior@aussie.zone
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      7 months ago

      Opened up DND Beyond to check since i remember rolling it before and its there, its between D8 and D10, the picture shows 2 dice

        • Urist@lemmy.ml
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          7 months ago

          Yup! Also one has to mind the order in which one rolls the dice. Since 10 and 5 could be either 05 or 50. As a bonus, if you roll them in order of “tens” to “ones”, getting 10 on the first dice has added suspense since the latter dice determines if it is going to count as a low roll of 0X (by rolling 1-9 on the next dice X) or if it is going to be a max roll of 100 (by rolling another 10).

    • The Cuuuuube@beehaw.org
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      7 months ago

      But why use Chatgpt for that? Why not a duck duck go action? I just don’t understand why we’re asking a LLM whose goal is consistency, not randomness, to do random

  • Rook@pawb.social
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    7 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
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        7 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
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      7 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
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    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.

    • kciwsnurb@aussie.zone
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      8 months ago

      The temperature scale, I think. You divide the logit output by the temperature before feeding it to the softmax function. Larger (resp. smaller) temperature results in a higher (resp. lower) entropy distribution.

        • kciwsnurb@aussie.zone
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          7 months ago

          Each row in the figure is a probability distribution over possible outputs (x-axis labels). The more yellow, the more likely (see the colour map on the right). With a small temperature (e.g., last row), all the probability mass is on 42. This is a low entropy distribution because if you sample from it you’ll constantly get 42, so no randomness whatsoever (think entropy as a measure of randomness/chaos). As temperature increases (rows closer to the first/topmost one), 42 is still the most likely output, but the probability mass gets dispersed to other possible outputs too (other outputs get a bit more yellow), resulting in higher entropy distributions. Sampling from such distribution gives you more random outputs (42 would still be frequent, but you’d get 37 or others too occasionally). Hopefully this is clearer.

          Someone in another reply uses the word “creativity” to describe the effect of temperature scaling. The more commonly used term in the literature is “diversity”.

    • The Octonaut@mander.xyz
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      8 months ago

      Temperature is basically how creative you want the AI to be. The lower the temperature, the more predictable (and repeatable) the response.

      • lolola
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        8 months ago

        Creativity is hot. That makes more sense, thanks.

  • Wirlocke
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    7 months ago

    I’m curious, is there actually so many 42’s in the system? (more than 69 sounds unlikely)

    What if the LLM is getting tripped up because 42 is always referred to as the answer to “the Ultimate Question of Life, the Universe, and Everything”.

    So you ask it a question like give a number between 1-100, it answers 42 because that’s the answer to “Everything”, according to it’s training data.

    Something similar happened to Gemini. Google discouraged Gemini from giving unsafe advice because it’s unethical. Then Gemini refused to answer questions about C++ because it’s considered “unsafe” (referring to memory management). But Gemini thinks C++ is “unsafe” (the normal meaning), therefore it’s unethical. It’s like those jailbreak tricks but from its own training set.

    • Corgana@startrek.website
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      7 months ago

      I’m curious, is there actually so many 42’s in the system?

      Sort of, it’s not actually picking a random number. It does not know what “random” means. It is analyzing the number of times the question “pick a random number” was asked and what the most common responses to that question looked like.

    • Glasgow@lemmy.ml
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      7 months ago

      I certainly hope that’s what happening or maybe it is actually the answer.