Comment by vidarh
11 days ago
> However, LLMs will not be able to represent ideas that it has not encountered before. It won't be able to come up with truly novel concepts, or even ask questions about them. Humans (some at least) have that unbounded creativity that LLMs do not.
There's absolutely no evidence to support this claim. It'd require humans to exceed the Turing computable, and we have no evidence that is possible.
If you tell me that trees are big, and trees are made of hard wood, I as a human am capable of asking whether trees feel pain. I don't think what you said is false and I am not familiar with computational theory to be able to debate it. People occasionally have novel creative insights that do not derive from past experience or knowledge, and that is what I think of when I think of creativity.
Humans created novel concepts like writing literally out of thin air. I like how the book "Guns, Steels, and Germs" describes that novel creative process and contrasts it via a disseminative derivation process.
> People occasionally have novel creative insights that do not derive from past experience or knowledge, and that is what I think of when I think of creativity.
If they are not derived from past experience or knowledge, then unless humans exceed the Turing computable, they would need to be the result of randomness in one form or other. There's absolutely no reason why an LLM can not do that. The only reason a far "dumber" pure random number generator based string generator "can't" do that is because it would take too long to chance on something coherent, but it most certainly would keep spitting out novel things. The only difference is how coherent the novel things are.
> If they are not derived from past experience or knowledge
Every animal is born with intuition, you missed that part.
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Wouldn't this insight derive from many past experiences of feeling pain yourself and the knowledge that others feel it too?
Turing computability is tangential to his claim, as LLMs are obviously not carrying out the breadth of all computable concepts. His claim can be trivially proven by considering the history of humanity. We went from a starting point of having literally no language whatsoever, and technology that would not have expanded much beyond an understanding of 'poke him with the pointy side'. And from there we would go on to discover the secrets of the atom, put a man on the Moon, and more. To say nothing of inventing language itself.
An LLM trained on this starting state of humanity is never going to do anything except remix basically nothing. It's never going to discover the secrets of the atom, or how to put a man on the Moon. Now whether any artificial device could achieve what humans did is where the question of computability comes into play, and that's a much more interesting one. But if we limit ourselves to LLMs, then this is very straight forward to answer.
> Turing computability is tangential to his claim, as LLMs are obviously not carrying out the breadth of all computable concepts
They don't need to. To be Turing complete a system including an LLM need to be able to simulate a 2-state 3-symbol Turing machine (or the inverse). Any LLM with a loop can satisfy that.
If you think Turing computability is tangential to this claim, you don't understand the implications of Turing computability.
> His claim can be trivially proven by considering the history of humanity.
Then show me a single example where humans demonstrably exceeding the Turing computable.
We don't even know any way for that to be possible.
"To be Turing complete a system including an LLM need to be able to simulate a 2-state 3-symbol Turing machine (or the inverse)."
And infinite memory. You forgot the infinite memory. And LLMs are extremely inefficient with memory. I'm not talking about the memory needed in the GPU to store the weights, but rather the ability of an LLM to remember whatever it's working on at the moment.
What could be stored as a couple of bits in a temporary variable is usually output as "Step 3: In the previous step we frobbed the junxer and got junx, and if you do junx + flibbity you get floopity"
And remember that this takes up a bunch of tokens. Without doing this (whether the LLM provider decides to let you see it or not, but still bill you for it), an LLM can't possibly execute an algorithm that requires iteration in the general case. For a more rigorous example, check apple's paper where an LLM failed to solve a tower of hanoi problem even when it had the exact algorithm to do so in context (apart from small instances of the problem for which the solution is available countless times).
This is akin to claiming that a tic-tac-toe game is turing complete since after all we could simply just modify it to make it not a tic tac toe game. It's not exactly a clever argument.
And again there are endless things that seem to reasonably defy turing computability except when you assume your own conclusion. Going from nothing, not even language, to richly communicating, inventing things with no logical basis for such, and so is difficult to even conceive as a computable process unless again you simply assume that it must be computable. For a more common example that rapidly enters into the domain of philosophy - there is the nature of consciousness.
It's impossible to prove that such is Turing computable because you can't even prove consciousness exists. The only way I know it exists is because I'm most certainly conscious, and I assume you are too, but you can never prove that to me, anymore than I could ever prove I'm conscious to you. And so now we enter into the domain of trying to computationally imagine something which you can't even prove exists, it's all just a complete nonstarter.
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I'd also add here that I think the current consensus among those in AI is implicit agreement with this issue. If we genuinely wanted AGI it would make vastly more sense to start from as little as possible because it'd ostensibly reduce computational and other requirements by many orders of magnitude, and we could likely also help create a more controllable and less biased model by starting from a bare minimum of first principles. And there's potentially trillions of dollars for anybody that could achieve this. Instead, we get everything dumped into token prediction algorithms which are inherently limited in potential.
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You are making a big assumption here, which is that LLMs are the main "algorithm" that the human brain uses. The human brain can easily be a Turing machine, that's "running" something that's not an LLM. If that's the case, we can say that the fact that humans can come up with novel concept does not imply that LLMs can do the same.
No, I am not assuming anything about the structure of the human brain.
The point of talking about Turing completeness is that any universal Turing machine can emulate any other (Turing equivalence). This is fundamental to the theory of computation.
And since we can easily show that both can be rigged up in ways that makes the system Turing complete, for humans to be "special", we would need to be able to be more than Turing complete.
There is no evidence to suggest we are, and no evidence to suggest that is even possible.
An LLM is not a universal Turing machine, though. It's a specific family of algorithms.
You can't build an LLM that will factorize arbitrarily large numbers, even in infinite time. But a Turing machine can.
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