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> Some of the complexity may be doing double duty. Since we have not succeeded in imitating even the most primitive brains, even though computationally we shou

> Some of the complexity may be doing double duty. Since we have not succeeded in imitating even the most primitive brains, even though computationally we should have enough juice by now, it would seem that complexity can't be discarded at all, no?

TeMPOraL 3y ago
> Since we have not succeeded in imitating even the most primitive brains, even though computationally we should have enough juice by now looks at the browser tab with GPT-4 in it looks back again here ... we didn't?
- AstralStorm 3y ago
  We didn't. Try to get ChatGPT through a maze a C. Elegans can solve in minutes. (That slow mostly because pond scum moves slowly.) Seriously, get it to successfully play through a text adventure maze game.
  - mschuster91 3y ago
    The problem with ChatGPT is it lacks the context depth for more complex tasks - but that is a computation resource limit, not a technical one.
  - TeMPOraL 3y ago
    > Seriously, get it to successfully play through a text adventure maze game. I did exactly that the other day in response to a different objection on a HN thread. Or at least similar enough. https://cloud.typingmind.com/share/c0a68cb2-5f59-4e83-b383-bcd7aad497f2 https://cloud.typingmind.com/share/c0a68cb2-5f59-4e83-b383-b... Now, the goal there wasn't to get it to solve a maze, but rather to see how it can come up with a plan of action and adjust it on the fly. But I see no reason a variant of that wouldn't work with a traditional maze game - provided you remember this is a stateless model without volatile memory, so it needs to be fed its memory with every request.
- MrBuddyCasino 3y ago
  No we haven't. ChatGPT is basically a sophisticated Markov chain. It is very good at pattern matching, but it has no understanding of anything, or its own will. People who think is even close to AGI are deluded, fooled by an elaborate Mechanical Turk. This is also the reason why its output sounds convincing, but is very often factually wrong.
  - TeMPOraL 3y ago
    I disagree, but that's beside the point here. You yourself narrowed the scope to: "imitating even the most primitive brains, even though computationally we should have enough juice by now" Which is kind of weird to claim today. GPT-4 may be the strongest counterexample to date, but it's far from the only one. Of course, you need to remember not to confuse the brain with attached peripherals. Just because we can't replicate a perfect worm or fly body, complete with bioelectrical and biomechanical components, doesn't mean we can't do better than their brains in silico.
    - mrtranscendence 3y ago
      GPT-4 does not "imitate" a "brain"; it does not function like a brain, nor is it even really analogous to a brain in any useful sense. What it imitates is human speech.
      - MrBuddyCasino 3y ago
        Thanks, I gave up halfway writing this.
      - TeMPOraL 3y ago
        "Imitating human speech" is not a trivial thing. You can't do it by a lookup table, or by a Markov chain. Not properly, not in open-ended, unscripted situations. It requires capabilities and structures that, if they aren't a world model and basic abstract reasoning skill, then they at least start to look strikingly similar in practice. This is where we are with GPT-4. It doesn't imitate speech. It imitates reasoning. And if it walks like a duck, and quacks like a duck, ... GPT-4 is a good example because it's pretty clear that the model isn't merely a stochastic parrot (or, if it is in some sense, then in that sense so are we). But it's not the only game in town. Not all generative transformers deal with language. All seem to be powerful association machines, drawing their capabilities from simple algorithms in absurdly high-dimensional spaces. There are many parallels you can draw to brains here, not the least of which is that the overall architecture is simple enough and scalable, that it's exactly the kind of thing evolution could reach and then get railroaded into building on.

TeMPOraL 3y ago

> Since we have not succeeded in imitating even the most primitive brains, even though computationally we should have enough juice by now looks at the browser tab with GPT-4 in it looks back again here ... we didn't?

AstralStorm 3y ago
We didn't. Try to get ChatGPT through a maze a C. Elegans can solve in minutes. (That slow mostly because pond scum moves slowly.) Seriously, get it to successfully play through a text adventure maze game.
- mschuster91 3y ago
  The problem with ChatGPT is it lacks the context depth for more complex tasks - but that is a computation resource limit, not a technical one.
- TeMPOraL 3y ago
  > Seriously, get it to successfully play through a text adventure maze game. I did exactly that the other day in response to a different objection on a HN thread. Or at least similar enough. https://cloud.typingmind.com/share/c0a68cb2-5f59-4e83-b383-bcd7aad497f2 https://cloud.typingmind.com/share/c0a68cb2-5f59-4e83-b383-b... Now, the goal there wasn't to get it to solve a maze, but rather to see how it can come up with a plan of action and adjust it on the fly. But I see no reason a variant of that wouldn't work with a traditional maze game - provided you remember this is a stateless model without volatile memory, so it needs to be fed its memory with every request.
MrBuddyCasino 3y ago
No we haven't. ChatGPT is basically a sophisticated Markov chain. It is very good at pattern matching, but it has no understanding of anything, or its own will. People who think is even close to AGI are deluded, fooled by an elaborate Mechanical Turk. This is also the reason why its output sounds convincing, but is very often factually wrong.
- TeMPOraL 3y ago
  I disagree, but that's beside the point here. You yourself narrowed the scope to: "imitating even the most primitive brains, even though computationally we should have enough juice by now" Which is kind of weird to claim today. GPT-4 may be the strongest counterexample to date, but it's far from the only one. Of course, you need to remember not to confuse the brain with attached peripherals. Just because we can't replicate a perfect worm or fly body, complete with bioelectrical and biomechanical components, doesn't mean we can't do better than their brains in silico.
  - mrtranscendence 3y ago
    GPT-4 does not "imitate" a "brain"; it does not function like a brain, nor is it even really analogous to a brain in any useful sense. What it imitates is human speech.
    - MrBuddyCasino 3y ago
      Thanks, I gave up halfway writing this.
    - TeMPOraL 3y ago
      "Imitating human speech" is not a trivial thing. You can't do it by a lookup table, or by a Markov chain. Not properly, not in open-ended, unscripted situations. It requires capabilities and structures that, if they aren't a world model and basic abstract reasoning skill, then they at least start to look strikingly similar in practice. This is where we are with GPT-4. It doesn't imitate speech. It imitates reasoning. And if it walks like a duck, and quacks like a duck, ... GPT-4 is a good example because it's pretty clear that the model isn't merely a stochastic parrot (or, if it is in some sense, then in that sense so are we). But it's not the only game in town. Not all generative transformers deal with language. All seem to be powerful association machines, drawing their capabilities from simple algorithms in absurdly high-dimensional spaces. There are many parallels you can draw to brains here, not the least of which is that the overall architecture is simple enough and scalable, that it's exactly the kind of thing evolution could reach and then get railroaded into building on.