Don’t believe the hype: AGI is far from inevitable | Radboud University
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Will AI soon surpass the human brain? If you ask employees at OpenAI, Google DeepMind and other large tech companies, it is inevitable. However, researchers at Radboud University and other institutes show new proof that those claims are overblown.

cross-posted from: https://lemmy.ml/post/20858435

Will AI soon surpass the human brain? If you ask employees at OpenAI, Google DeepMind and other large tech companies, it is inevitable. However, researchers at Radboud University and other institutes show new proof that those claims are overblown and unlikely to ever come to fruition. Their findings are published in Computational Brain & Behavior today.

  • @[email protected]
    9•2 days ago

    A breakthrough in quantum computing wouldn’t necessarily help. QC isn’t faster than classical computing in the general case, it just happens to be for a few specific algorithms (e.g. factoring numbers). It’s not impossible that a QC breakthrough might speed up training AI models (although to my knowledge we don’t have any reason to believe that it would) and maybe that’s what you’re referring to, but there’s a widespread misconception that Quantum computers are essentially non-deterministic turing machines that “evaluate all possible states at the same time” which isn’t the case.

    • 𝙲𝚑𝚊𝚒𝚛𝚖𝚊𝚗 𝙼𝚎𝚘𝚠
      8•2 days ago

      I was more hinting at that through conventional computational means we’re just not getting there, and that some completely hypothetical breakthrough somewhere is required. QC is the best guess I have for where it might be but it’s still far-fetched.

      But yes, you’re absolutely right that QC in general isn’t a magic bullet here.

      • @[email protected]
        3•2 days ago

        the limitation is specifically using the primary machine learning technique, same one all chatbots use at places claiming to pursue agi, which is statistical imitation, is np-hard.

        • 𝙲𝚑𝚊𝚒𝚛𝚖𝚊𝚗 𝙼𝚎𝚘𝚠
          2•1 day ago

          Not just that, they’ve proven it’s not possible using any tractable algorithm. If it were you’d run into a contradiction. Their example uses basically any machine learning algorithm we know, but the proof generalizes.

          • @[email protected]
            1•1 day ago

            via statistical imitation. other methods, such as solving and implementing by first principles analytically, has not been shown to be np hard. the difference is important but the end result is still no agigpt in the foreseeable and unforeseeable future.

      • @[email protected]
        6•2 days ago

        Yeah thought that might be the case! It’s just a thing that a lot of people have misconceptions about so it’s something that I have a bit of a knee jerk reaction to.