• El Barto@lemmy.world
    link
    fedilink
    English
    arrow-up
    2
    ·
    1 year ago

    Oh but those pattern recognition examples are about machine learning, right? Which I guess it’s a form of AI.

    • TWeaK@lemm.ee
      link
      fedilink
      English
      arrow-up
      1
      ·
      1 year ago

      Perhaps, but at best it’s still a very basic form of AI, and maybe shouldn’t even be called AI. Before things like ChatGPT, the term “AI” meant a full blown intelligence that could pass a Turing test, and a Turing test is meant to prove actual artificial thought akin to the level of human thought - something beyond following mere pre-programmed instructions. Machine learning doesn’t really learn anything, it’s just an algorithm that repeatedly measures and then iterates to achieve an ideal set of values for desired variables. It’s very clever, but it doesn’t really think.

      • El Barto@lemmy.world
        link
        fedilink
        English
        arrow-up
        1
        ·
        1 year ago

        I have to disagree with you in the machine learning definition. Sure, the machine doesn’t think in those circumstances, but it’s definitely learning, if we go by what you describe what they do.

        Learning is a broad concept, sure. But say, if a kid is learning to draw apples, then is successful to draw apples without help in the future, we could way that the kid achieved “that ideal set of values.”

        • TWeaK@lemm.ee
          link
          fedilink
          English
          arrow-up
          1
          ·
          1 year ago

          Machine learning is a simpler type of AI than an LLM, like ChatGPT or AI image generators. LLM’s incorporate machine learning.

          In terms of learning to draw something, after a child learns to draw an apple they will reliably draw an apple every time. If AI “learns” to draw an apple it tends to come up with something subtley unrealistic, eg the apple might have multiple stalks. It fits the parameters it’s learned about apples, parameters which were prescribed by its programming, but it hasn’t truly understood what an apple is. Furthermore, if you applied the parameters it learned about apples to something else, it might completely fail to understand it all together.

          A human being can think and interconnect its throughts much more intricately, we go beyond our basic programming and often apply knowledge learned in one thing to something completely different. Our understanding of things is much more expansive than AI. AI currently has the basic building blocks of understanding, in that it can record and recall knowledge, but it lacks the full amount of interconnections between different pieces and types of knowledge that human beings develop.

          • El Barto@lemmy.world
            link
            fedilink
            English
            arrow-up
            1
            ·
            edit-2
            1 year ago

            Thanks. I understood all that. But my point is that machine learning is still learning, just like machine walking is still walking. Can a human being be much better at walking than a machine? Sure. But that doesn’t mean that the machine isn’t walking.

            Regardless, I appreciate your comment. Interesting discussion.