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Comment by soulofmischief | Hacker News Reader

Ultimately you are just a system who maintains homeostasis by modeling your environment and reprojecting it to find patterns which can be used to make actions with predictable outcomes. Is this intelligence? Is there only one correct way to achieve this goal?

What do you believe intelligence to be?

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Ultimately we're just a collection of atoms obeying the laws of physics, but reducing all the complexity that entails doesn't really accomplish anything

This is my frustration put really well. When people talk about how humans are also just a form of LLM (not that the above comment did exactly that). That might even be true, but simplifying things to that degree doesn't help actually discuss what is going on. The original comment is as far as I know correct... while I don't have a PhD some of my undergraduate work was in control theory and ML, and it works really well. The underlying methods we used were from NASA in the late 70s.. surely there is something more in the field no?

You can look at very small creatures on earth and think "surely there is more to a human than to this ant". And sure, there is, but also, there isn't. Just as basic life evolves into more complex life, why shouldn't the underlying methods from the NASA in the late 70s evolve into ChatGPT and eventually AGI?

Simplifying things to this degree can show how you get from A to B.

I’m not the only one who thinks there is something missing though. That simplification does work to show how to get from A to B, but I don’t think it is analogous when we don’t really understand how we go to human intelligence. None of us were there. All I am saying is that simplifying even mammalian intelligence down to just an LLM doesn’t explain much to me. It might be the case that old 70s math proofs from NASA evolve into a mechanical intelligence maybe? I just personally think that isn’t the case. Humans run on a lot less overall power (though biological necessities like bathrooms and food are real), we also can learn even from less text than a machine and infer from experience. That might not convince you, or you might have your own ideas about what intelligence is.

We can see how an ant is a more primitive form of the same kind of thing that a human is, and though they're not on the same evolutionary path, we can see how humans evolved from the most primitive forms of life, because we know what the endpoint looks like.

We don't know what 70s AI and ChatGPT will evolve into. That's why everyone keeps debating and prognosticating about it, because nobody actually knows. But whatever people mean by AGI, we don’t know if it will or can evolve from the AI platforms that have come before.

We do know that the thing that evolved into ChatGPT is entirely different from primitive cellular life, so there's no reason to believe that ChatGPT will keep evolving into some kind of humanistic, self-aware intelligence.

What frustrates me is when people say "neural networks cannot show intelligence because they are just a succession of linear layers", and methods that exist since the 70s". I don't understand this argument, and how this has anything to do with intelligence.

I’m not saying they can’t show intelligence. I am saying that the techniques are very old, throwing more hardware seems to have done wonders. It’s been surprising to see how far it’s come. I don’t think that simplifying intelligence in humans and saying we are LLMs helps the conversation. That along with that these techniques being used while they’ve clearly been improved are fairly old. From an engineering standpoint it leaves me wondering if there are not more elegant solutions. That nature actually is fairly cool, it doesn’t help the convo to downplay wetware I think.

There's a good summary in the Introduction to Kevin Murphy's second tome [1]. He quotes Josh Tenenbaum, who said: "Intelligence is not just about pattern recognition and function approximation. It’s about modeling the world".

I agree, and I think Goodman & Tenennaum [2] is a great place to see other things that may pop up in the road to AGI. LLMs are great, but they do too much at once. I think moving towards AGI requires some form of symbolic reasoning, possibly combined with LLMs, which may play the role of intuition and kitchen-sink memory.

[1] https://probml.github.io/pml-book/book2.html

[2] https://probmods.org

Modelling the world is function approximation: the world is the function and the model is the approximation.

Do we know for sure that LLMs can't possibly be doing symbolic reasoning of some sort, internally? I thought we couldn't really interpret them yet.

There's mounting evidence LLMs do appear to form models of the real world https://thegradient.pub/othello/

all claims and questions in your answer are still open research and full of inconclusive evidence. Ultimately all of this leads down the spiral to the question about ship of Theseus. I guess, we will find out!

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