I’m usually the one saying “AI is already as good as it’s gonna get, for a long while.”

This article, in contrast, is quotes from folks making the next AI generation - saying the same.

  • cron@feddit.org
    link
    fedilink
    English
    arrow-up
    0
    ·
    11 days ago

    It’s absurd that some of the larger LLMs now use hundreds of billions of parameters (e.g. llama3.1 with 405B).

    This doesn’t really seem like a smart usage of ressources if you need several of the largest GPUs available to even run one conversation.

      • cron@feddit.org
        link
        fedilink
        English
        arrow-up
        0
        ·
        11 days ago

        I don’t think your brain can be reasonably compared with an LLM, just like it can’t be compared with a calculator.

        • GetOffMyLan@programming.dev
          link
          fedilink
          English
          arrow-up
          0
          ·
          11 days ago

          LLMs are based on neural networks which are a massively simplified model of how our brain works. So you kind of can as long as you keep in mind they are orders of magnitude more simple.

          • utopiah@lemmy.world
            link
            fedilink
            English
            arrow-up
            0
            ·
            10 days ago

            At some point it becomes so “simplified” it’s arguably just not the same thing, even conceptually.

            • GetOffMyLan@programming.dev
              link
              fedilink
              English
              arrow-up
              0
              arrow-down
              1
              ·
              edit-2
              9 days ago

              It is conceptually the same thing. A series of interconnected neurons with a firing threshold and weighted connections.

              The simplification comes with how the information is transmitted and how our brain learns.

              Many functions in the human body rely on quantum mechanical effects to function correctly. So to simulate it properly each connection really needs to be its own super computer.

              But it has been shown to be able to encode information in a similar way. The learning the part is not even close.

              • utopiah@lemmy.world
                link
                fedilink
                English
                arrow-up
                1
                ·
                5 days ago

                It is conceptually the same thing. […] The learning the part is not even close.

                Well… isn’t the “learning part” precisely the point? I don’t think anybody is excited about brains as “just” a computational device, rather the primary function of a brain is … learning.

                • GetOffMyLan@programming.dev
                  link
                  fedilink
                  English
                  arrow-up
                  1
                  ·
                  4 days ago

                  No, we are nowhere close to learning as the human brain does. We don’t even really understand how it does at all.

                  The point is to encode solutions to problems that we can’t solve with standard programming techniques. Like vision, speech recognition and generation.

                  These problems are easy for humans and very difficult for computers. The same way maths is super easy for computers compared to humans.

                  By applying techniques our neurones use computer vision and speech have come on in leaps and bounds.

                  We are decades from getting anything close to a computer brain.

                  • utopiah@lemmy.world
                    link
                    fedilink
                    English
                    arrow-up
                    1
                    ·
                    2 days ago

                    No, we are nowhere close to learning as the human brain does. We don’t even really understand how it does at all.

                    Sorry then if I sound like a broken record but again, doesn’t that mean that the analogy itself is flawed? If the goal remain the same but there is close to no explanatory power, even if we do get pragmatically useful result (i.e. it “works” in some useful cases) it’s basically “just” inspiration, which is nice but is basically branding more than anything else.