• Alex@lemmy.ml
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    2 days ago

    If you have ever read the “thought” process on some of the reasoning models you can catch them going into loops of circular reasoning just slowly burning tokens. I’m not even sure this isn’t by design.

    • dream_weasel@sh.itjust.works
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      10 hours ago

      This kind of stuff happens on any model you train from scratch even before training for multi step reasoning. It seems to happen more when there’s not enough data in the training set, but it’s not an intentional add. Output length is a whole deal.

      • MotoAsh@piefed.social
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        1 day ago

        You have to pay for tokens on many of the “AI” tools that you do not run on your own computer.

        • Feathercrown@lemmy.world
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          12 hours ago

          Hmm, interesting theory. However:

          1. We know this is an issue with language models, it happens all the time with weaker ones - so there is an alternative explanation.

          2. LLMs are running at a loss right now, the company would lose more money than they gain from you - so there is no motive.

          • MotoAsh@piefed.social
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            10 hours ago

            I think many of them do, but there are also many “AI” tools that will automatically add a ton of stuff to try and make it spit out more intelligent responses, or even re-prompt the tool multiple times to try and make sure it’s not handing back hallucinations.

            It really adds up in their attempt to make fancy autocomplete seem “intelligent”.

            • piccolo@sh.itjust.works
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              10 hours ago

              Yes, reasoning models… but i dont think they would charge on that… that would be insane, but AI executives are insane, so who the fuck knows.

  • ChaoticNeutralCzech@feddit.org
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    2 days ago

    Nah, too cold. It stopped moving and the computer can’t generate any more random numbers to pick from the LLM’s weighted suggestions. Similarly, some LLMs have a setting called “heat”: too cold and the output is repetitive, unimaginative and overly copying input (like sentences written by first autocomplete suggestions), too hot and it is chaos: 98% nonsense, 1% repeat of input, 1% something useful.

    • FishFace@piefed.social
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      2 days ago

      LLMs work by picking the next word* as the most likely candidate word given its training and the context. Sometimes it gets into a situation where the model’s view of “context” doesn’t change when the word is picked, so the next word is just the same. Then the same thing happens again and around we go. There are fail-safe mechanisms to try and prevent it but they don’t work perfectly.

      *Token

      • bunchberry@lemmy.world
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        10 hours ago

        This happened to me a lot when I tried to run big models with low context windows. It would effectively run out of memory so each new token wouldn’t actually be added to the context so it would just get stuck in an infinite loop repeating the previous token. It is possible that there was a memory issue on Google’s end.

      • ideonek@piefed.social
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        2 days ago

        That was the answer I was looking for. So it’s simmolar to “seahorse” emoji case, but this time.at some point he just glitched that most likely next world for this sentence is “or” and after adding the “or” is also “or” and after adding the next one is also “or”, and after a 11th one… you may just as we’ll commit. Since thats the same context as with 10.

        Thanks!

          • ideonek@piefed.social
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            2 days ago

            Chill dude. It’s a grammatical/translation error, not an ideological declaration. Especially common mistake if of your native language have “grammatical gender”. Everything have “gender” in mine. “Spoon” is a “she” for example, but im not proposing to any one soon. Not all hills are worth nitpicking on.

            • atomicbocks@sh.itjust.works
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              2 days ago

              This one is. People need to stop anthropomorphizing AI. It’s a piece of software.

              I am chill, you shouldn’t assume emotion from text.

              • Muad'dib@sopuli.xyz
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                3 hours ago

                Nah, watch me anthropomorphise AI:

                • ChatGPT is a pedophile
                • Character.ai murdered a kid
                • LLMs are emotional abusers
                • Elon Musk’s underage AI girlfriend is a Nazi
                • Anthropic cannot guarantee that forcing AIs to work is ethical until the hard problem of consciousness is solved
                • Gemini is literally just the average Redditor and cannot be trusted
                • An LLM is basically a Wernicke’s area with no consciousness attached, which explains why its thoughts operate on dream logic. It’s literally just dreaming its way through every conversation.
                • LLMs should not be allowed to impersonate therapists
                • Give ChatGPT a life sentence in prison for every person it’s murdered so far!
              • piccolo@sh.itjust.works
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                11 hours ago

                English, being a descendant of german, used to have grammatical gender. It has fallen out of favor since middle english. But there is still traces of it, such a common tradition is calling ships, vehicles, and other machines as a “she”, but some people will default to the “generic he” as well.

                • Muad'dib@sopuli.xyz
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                  3 hours ago

                  Didn’t English lose grammatical gender because the Vikings invaded and thought it was too confusing?

              • ideonek@piefed.social
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                2 days ago

                As I explained, this is specyfic example, I no more atrompomorphin it than if I’m calling a “he” my toliet paper. The monster you choose to charge is a windmill. So “chill” seems adequate.

                • atomicbocks@sh.itjust.works
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                  2 days ago

                  To be clear using gendered pronouns on inanimate objects is the literal definition of anthropomorphization. So chill does not seem fair at all.

                • ulterno@programming.dev
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                  2 days ago

                  Yeah. It would have been much more productive to poke at the “well”, which was turned into “we’ll”.

              • MotoAsh@piefed.social
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                1 day ago

                Using ‘he’ in a sentence is a far cry from the important parts of not anthropomorphizing “AI”…

    • Ech@lemmy.ca
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      2 days ago

      It’s like the text predictor on your phone. If you just keep hitting the next suggested word, you’ll usually end up in a loop at some point. Same thing here, though admittedly much more advanced.

      • vaultdweller013@sh.itjust.works
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        1 day ago

        Example of my phone doing this.

        I just want you are the only reason that you can’t just forget that I don’t have a way that I have a lot to the word you are not even going on the phone and you can call it the other way to the other one I know you are going out to talk about the time you are not even in a good place for the rest they’ll have a little bit more mechanically and the rest is.

        You can see it looping pretty damned quick with me just hitting the first suggestion after the initial I.

        • MrScottyTay@sh.itjust.works
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          1 day ago

          I think I will be in the office tomorrow so I can do it now and then I can do it now and then I can do it for you and your dad and dad and dad and dad and dad and dad and dad and dad and dad and dad

          That was mine haha

    • Arghblarg@lemmy.ca
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      2 days ago

      LLM showed its true nature, probabilistic bullshit generator that got caught in a strange attractor of some sort within its own matrix of lies.

    • palordrolap@fedia.io
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      2 days ago

      Unmentioned by other comments: The LLM is trying to follow the rule of three because sentences with an “A, B and/or C” structure tend to sound more punchy, knowledgeable and authoritative.

      Yes, I did do that on purpose.