“Our primary conclusion across all scenarios is that without enough fresh real data in each generation of an autophagous loop, future generative models are doomed to have their quality (precision) or diversity (recall) progressively decrease,” they added. “We term this condition Model Autophagy Disorder (MAD).”

Interestingly, this might be a more challenging problem as we increase the use of generative AI models online.

  • argv_minus_one@beehaw.org
    link
    fedilink
    English
    arrow-up
    43
    ·
    1 year ago

    Note that humans do not exhibit this property when trained on other humans, so this would seem to prove that “AI” isn’t actually intelligent.

    • PenguinTD@lemmy.ca
      link
      fedilink
      English
      arrow-up
      13
      ·
      1 year ago

      do we even need to prove this? Like anyone study a bit how generative AI works know it’s not intelligent.

    • h3ndrik@feddit.de
      link
      fedilink
      English
      arrow-up
      6
      ·
      1 year ago

      Wasn’t the echo chambers during the covid pandemic kind of proof that humans DO exhibit the same property? A good amount will start repeating stuff about nanoparticles and some black lint in a mask are worms that will control your brain?

    • ParsnipWitch@feddit.de
      link
      fedilink
      English
      arrow-up
      6
      ·
      1 year ago

      Current AI is not actually “intelligent” and, as far as I know, not even their creators directly describe them as that. The programs and models existing at the moment aren’t capable of abstract thinking oder reasoning and other processes that make an intelligent being or thing intelligent.

      The companies involved are certainly eager to create something like a general intelligence. But even when they reach that goal, we don’t know yet if such an AGI would even be truly intelligent.

    • echo@sopuli.xyz
      link
      fedilink
      English
      arrow-up
      5
      ·
      edit-2
      1 year ago

      I don’t think LLM’s are intelligent, but “does it work the same as humans” is a really bad way to judge something’s intelligence

      • frog 🐸@beehaw.org
        link
        fedilink
        English
        arrow-up
        14
        ·
        1 year ago

        Even if we look at other animals, when they learn by observing other members of their own species, they get more competent rather than less. So AIs are literally the only thing that get worse when trained on their own kind, rather than better. It’s hard to argue they’re intelligent if the answer to “does it work the same as any other lifeform that we know of?” is “no”.

        • FaceDeer@kbin.social
          link
          fedilink
          arrow-up
          2
          ·
          1 year ago

          Are there any animals that only learn by observing the outputs of members of their own species? Or is it a mixture of that and a whole bunch of their own experiences with the outside world?

          • frog 🐸@beehaw.org
            link
            fedilink
            arrow-up
            4
            ·
            1 year ago

            Humans (and animals) learn through a combination of their own experiences and observing the experiences of others. But this actually proves my point: if you feed an AI its own experiences (content it has created in response to prompts) and the experiences of other AIs (content they have produced in response to prompts), it cycles itself into oblivion. This is ultimately because it cannot create anything new.

            This is why Model Autophagy Disease occurs, I think. Humans, when put in repetitive scenarios, will actively work to create new stimuli to respond to. This varies from livening up a boring day by doing something ridiculous, to hallucinating when kept in extreme sensory deprivation. The human mind’s defence against repetitive stimuli is to literally create something new. But the AI’s can’t do that. They literally can’t. They can’t create anything that doesn’t have a basis in their training data, and when exposed only to iterations of their own training data (which is ultimately what all AI-generated content is: iterations of the training data), there is no process that allows them to break out of that repetitive cycle. They end up just spiralling inwards.

            From a certain perspective, AI’s are therefore essentially parasites. They cannot progress without sucking in more human-generated content. They aren’t self-sustaining on their own, because they literally cannot create the new ideas needed to prevent degradation of their own data sets.

            From your other comments here, it seems like you’re imagining a fully conscious mind sitting alone in a box, with nothing to react to. But that’s not the case: AIs aren’t sapient, going mad from a lack of stimulation. They are completely dormant until prompted to do something, and then they create an output that is statistically likely from the data set they’ve been trained on. If you add no new data, the AI doesn’t change. It doesn’t seek new stimuli. It doesn’t create new ideas while waiting for someone to prompt it. The only way it can change and create anything new is if it’s given more human-generated content to work with. If you give it content from other AI’s, that alters the statistical probabilities behind its output. If the AIs were actually conscious minds sitting alone in boxes, then exposing them to content created by other AIs would, in fact, be new stimuli that could generate new ideas, in the same way that a lonely human meeting another lonely human would quickly strike up a conversation and get all kinds of ideas.

            • theneverfox@pawb.social
              link
              fedilink
              arrow-up
              1
              ·
              1 year ago

              You’re caught up in an idea that has been going around since long before any AI systems had been built

              Humans rarely, if ever, produce something new. We stumble upon a concept or apply one idea to another thing

              Neural networks are carefully distilled entropy. They have no subjective biases and no foundation - they’re so good at being original that they default to things useless to humans.

              I like to think of training like a mold, or a filter. You only want things in the right shape to come through - the more you train, the more everything coming through looks the same.

          • lol3droflxp@kbin.social
            link
            fedilink
            arrow-up
            2
            ·
            1 year ago

            I mean, it’s always a mixture but yes, animals can learn new behaviours purely by watching (corvids and monkeys for example).

            • FaceDeer@kbin.social
              link
              fedilink
              arrow-up
              1
              ·
              1 year ago

              “It’s always a mixture” is the key part, though. We haven’t run an experiment like this on a human or animal (and even if it were practical to do so it’d probably be horribly abusive).

    • FaceDeer@kbin.social
      link
      fedilink
      arrow-up
      2
      ·
      1 year ago

      Humans are not entirely trained on other humans, though. We learn plenty of stuff from our environment and experiences. Note this very important part of the primary conclusion:

      without enough fresh real data in each generation

        • FaceDeer@kbin.social
          link
          fedilink
          arrow-up
          3
          ·
          edit-2
          1 year ago

          Dogs can do math and I’m quite sure I’ve never taught my dog that deliberately.

          Even for humans learning it, I would expect that most of our understanding of math comes from everyday usage of it rather than explicit rote training.

      • ParsnipWitch@feddit.de
        link
        fedilink
        English
        arrow-up
        5
        ·
        1 year ago

        The reason is different from what is happening with AI, though. Sensory deprivation or extreme isolation and the Ganzfeld effect lead to hallucinations because our brain seems to have to constantly react to stimuli in order to keep functioning. Our brain starts creating things from imagination.

        With AI it is the other way around. They lose information when presented with the same data again and again because their statistical models look for probabilities.