• andallthat@lemmy.world
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    2 months ago

    Basically, model collapse happens when the training data no longer matches real-world data

    I’m more concerned about LLMs collaping the whole idea of “real-world”.

    I’m not a machine learning expert but I do get the basic concept of training a model and then evaluating its output against real data. But the whole thing rests on the idea that you have a model trained with relatively small samples of the real world and a big, clearly distinct “real world” to check the model’s performance.

    If LLMs have already ingested basically the entire information in the “real world” and their output is so pervasive that you can’t easily tell what’s true and what’s AI-generated slop “how do we train our models now” is not my main concern.

    As an example, take the judges who found made-up cases because lawyers used a LLM. What happens if made-up cases are referenced in several other places, including some legal textbooks used in Law Schools? Don’t they become part of the “real world”?

    • Khanzarate@lemmy.world
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      2 months ago

      No, because there’s still no case.

      Law textbooks that taught an imaginary case would just get a lot of lawyers in trouble, because someone eventually will wanna read the whole case and will try to pull the actual case, not just a reference. Those cases aren’t susceptible to this because they’re essentially a historical record. It’s like the difference between a scan of the declaration of independence and a high school history book describing it. Only one of those things could be bullshitted by an LLM.

      Also applies to law schools. People do reference back to cases all the time, there’s an opposing lawyer, after all, who’d love a slam dunk win of “your honor, my opponent is actually full of shit and making everything up”. Any lawyer trained on imaginary material as if it were reality will just fail repeatedly.

      LLMs can deceive lawyers who don’t verify their work. Lawyers are in fact required to verify their work, and the ones that have been caught using LLMs are quite literally not doing their job. If that wasn’t the case, lawyers would make up cases themselves, they don’t need an LLM for that, but it doesn’t happen because it doesn’t work.

      • thedruid@lemmy.world
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        2 months ago

        It happens all the time though. Made up and false facts being accepted as truth with no veracity.

        So hard disagree.

        • Khanzarate@lemmy.world
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          2 months ago

          The difference is, if this were to happen and it was found later that a court case crucial to the defense were used, that’s a mistrial. Maybe even dismissed with prejudice.

          Courts are bullshit sometimes, it’s true, but it would take deliberate judge/lawyer collusion for this to occur, or the incompetence of the judge and the opposing lawyer.

          Is that possible? Sure. But the question was “will fictional LLM case law enter the general knowledge?” and my answer is “in a functioning court, no.”

          If the judge and a lawyer are colluding or if a judge and the opposing lawyer are both so grossly incompetent, then we are far beyond an improper LLM citation.

          TL;DR As a general rule, you have to prove facts in court. When that stops being true, liars win, no AI needed.

  • Grandwolf319@sh.itjust.works
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    2 months ago

    Maybe, but even if that’s not an issue, there is a bigger one:

    Law of diminishing returns.

    So to double performance, it takes much more than double of the data.

    Right now LLMs aren’t profitable even though they are more efficient compared to using more data.

    All this AI craze has taught me is that the human brain is super advanced given its performance even though it takes the energy of a light bulb.

    • AItoothbrush@lemmy.zip
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      2 months ago

      Its very efficient specifically in what it does. When you do math in your brain its very inefficient the same way doing brain stuff on a math machine is.

    • rottingleaf@lemmy.world
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      2 months ago

      All this AI craze has taught me is that the human brain is super advanced given its performance even though it takes the energy of a light bulb.

      Seemed superficially obvious.

      Human brain is a system optimization of which took energy of evolution since start of life on Earth.

      That is, infinitely bigger amount of data.

      It’s like comparing a barrel of oil to a barrel of soured milk.

  • leftzero@lemmynsfw.com
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    2 months ago

    Obviously, yes.

    They knew this when they poisoned the well¹ (photocopy of a photocopy and all that), but they’re in it for the fast buck and will scamper off with the money once they think the bubble is about to burst.


    1.– Well, some of them might have drunk their own coolaid, and will end up having an intimate face to face meeting with some leopards…

  • Opinionhaver@feddit.uk
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    2 months ago

    Artificial intelligence isn’t synonymous with LLMs. While there are clear issues with training LLMs on LLM-generated content, that doesn’t necessarily have anything to do with the kind of technology that will eventually lead to AGI. If AI hallucinations are already often obvious to humans, they should be glaringly obvious to a true AGI - especially one that likely won’t even be based on an LLM architecture in the first place.

    • BananaTrifleViolin@lemmy.world
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      2 months ago

      I’m not sure why this is being downvoted—you’re absolutely right.

      The current AI hype focuses almost entirely on LLMs, which are just one type of model and not well-suited for many of the tasks big tech is pushing them into. This rush has tarnished the broader concept of AI, driven more by financial hype than real capability. However, LLM limitations don’t apply to all AI.

      Neural network models, for instance, don’t share the same flaws, and we’re still far from their full potential. LLMs have their place, but misusing them in a race for dominance is causing real harm.

  • doodledup@lemmy.world
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    2 months ago

    Most LLMs seed their output so they can recognize whether something was created by them. I can see how there will be common standards for this and every LLM as it’s in the best interest of every commercial LLM to know whether something is LLM output or not.

    • Khanzarate@lemmy.world
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      2 months ago

      Nah that means you can ask an LLM “is this real” and get a correct answer.

      That defeats the point of a bunch of kinds of material.

      Deepfakes, for instance. International espionage, propaganda, companies who want “real people”.

      A simple is_ai checkbox of any kind is undesirable, but those sources will end back up in every LLM, even one that was behaving and flagging its output.

      You’d need every LLM to do this, and there’s open source models, there’s foreign ones. And as has already been proven, you can’t rely on an LLM detecting a generated product without it.

      The correct way to do it would be to instead organize a not-ai certification for real content. But that would severely limit training data. It could happen once quantity of data isn’t the be-all end-all for a model, but I dunno when when or if that’ll be the case.