I know current learning models work a little like neurons but why not just make a sim that works exactly like how we understand neurons work

  • Phanatik@kbin.social
    link
    fedilink
    arrow-up
    1
    ·
    2 months ago

    I mainly disagree with the final statement on the basis that the LLMs are more advanced predictive text algorithms. The way they’ve been set up with a chatbox where you’re interacting directly with something that attempts human-like responses, gives off the misconception that the thing you’re talking to is more intelligent than it actually is. It gives off a strong appearance of intelligence but at the end of the day, it predicts the next word in a sentence based on what was said previously but it doesn’t do that good job of comprehending what exactly it’s telling you. It’s very confident when it gives responses which also means when it’s wrong, it’s very confidently delivering the incorrect response.

    • rtfm_modular@lemmy.world
      link
      fedilink
      arrow-up
      0
      ·
      2 months ago

      Talk to anyone who consumes Fox News daily and you’ll get incorrect predictive text generated quite confidently. You may also deny them their intelligence and lack of humanity with the fallacies they uphold.

      I also think intelligence is a gradient—is an ant intelligent? What about a dog? Chimp? Who gets to draw the line?

      It very may be a very complex predictive text generator that hallucinates but I’m concerned that it minimizes its capabilities for better or worse—Its ability to maintain context and has enough plasticity to reason and change its response points to something more, even if we’re at an early stage.

      • Phanatik@kbin.social
        link
        fedilink
        arrow-up
        1
        ·
        2 months ago

        What you’re alluding to is the Turing test and it hasn’t been proven that any LLM would pass it. At this moment, there are people who have failed the inverse Turing test, being able to acerrtain whether what they’re speaking to is a machine or human. The latter can be done and has been done by things less complex than LLMs and isn’t proof of an LLMs capabilities over more rudimentary chatbots.

        You’re also suggesting that it minimises the complexity of its outputs. My determination is that what we’re getting is the limit of what it can achieve. You’d have to prove that any allusion to higher intelligence can’t be attributed to coercion by the user or it’s just hallucinating based on imitating artificial intelligence from media.

        There are elements of the model that are very fascinating like how it organises language into these contextual buckets but this is still a predictive model. Understanding that certain words appear near each other in certain contexts is hardly intelligence, it’s a sophisticated machine learning algorithm.