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Chomsky on what ChatGPT is good for (2023)

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Re: Chomsky on what ChatGPT is good for (2023)

#281

Earlier quoted context omitted.

> The big lesson from the AI development in the last 10 years from me has been "I guess humans really aren't so special after all" Instead I would take the opposite take. How wonderful is it, that with naturally evolved processes and neural structures, have we been able to create what we have. Van Gogh’s paintings came out of the human brain. The Queens of the Skies - hundreds of tons of metal and composites - flying…

"I guess humans really aren't so special after all" This is a crazy take to me. As compared to what? The machines that we built? Until we discover comparably intelligent life in the universe I think it's fair to say that we are indeed very special.

You know how many old sci-fi settings pictured aliens as bipedal furry animals or lizards? Even to go from that to realistically-intelligent swarms of insects is already difficult.

(Of course, there’s plenty of sci-fi where conscious entities manifest themselves as abstract balls of pure energy or the like; except for some reason those balls still think in the same way we do, get assigned the same motivations, sometimes even speak our language, etc., which makes it, in a way, even less realistic than the walking and talking human-cat hybrid you’d see in Elder Scrolls.)

Whenever we ponder questions of intelligence and consciousness, the same pitfall awaits.

Since we don’t have an objective definition of consciousness or intelligence (and in all likelihood we can’t have one, because any formal attempt at such wouldn’t get very far due to being attempted by the same thing that’s being defined), the only one that makes sense is, in crude language, “something like what we are”. There’s a vague feeling that it has to do with free will, self-awareness, etc.; however, all of it is also influenced by the nature of us being all parts of some big figurative anthill—assuming your sense of self only arises as you model yourself against the other (starting with your parents/caretakers and on), a standalone human cannot be self-aware in the way we are if it evolved in an emptiness without others—i.e., it would not possess human intelligence; supported by our natural-scientific observations rejecting the possibility of a being of this shape and form ever evolving in the first place.

In other words, the more different some kind of intelligence is from ours, the less it would look like intelligence to us—which makes the search for alien intelligence in space somewhat tragically futile (if it exists, we wouldn’t recognize it unless it just happens to be like us), but opens up exciting opportunities for finding alien but not-too-alien intelligence right on this planet (almost Douglas Adams style, minus dolphins speaking English).

There’s an extra trick when it comes to LLMs. In case of alien life, the possibility of a radically different kind of consciousness producing output that closely mimics our own is almost impossible (if our prior assumption is correct, then for all intents and purposes truly alien, non-meatbag-scale kind of intelligence might not be able to recognize ours in the first place, just like we wouldn’t recognize alien intelligence). However, the LLMs are designed to mimic the most social aspect of our behavior, our communication aimed at fellow humans; so when an LLM produces sufficiently human-like output—even if it has a very different kind of consciousness[0] or no consciousness at all (more likely, though as we concluded above we can’t distinguish between the two cases anyway)—our minds are primed to see it as a manifestation of [which would be human-like] intelligence, even if there’s nothing that would suggest such judging by the way it’s created (which is radically different from the way we’ve been creating intelligent life so far, wink-wink), by the substrate it runs on, if not by the way it actually works (which per our conclusion above we might never be able to conclusively determine about our own minds, without resorting to unfalsifiable philosophical assumptions for at least some aspects of it).

So yes, I’d say humans are special, if nothing else then because by the only usable (if somewhat circular) definition of what we are there’s absolutely nothing like us around, and in all likelihood can never be. (That’s not to say that something not like us isn’t special in its own way—I mean, think of the dolphins!—but given we, due to not being it, would not be able to properly understand it, it just never hits the same.)

[0] Which if true would be completely asocial (given it neither exists in groups nor depends on others for survival) and therefore drastically different from ours.

Re: Chomsky on what ChatGPT is good for (2023)

#283
post #248
post #247

Earlier quoted context omitted.

> it has made me question whether such a thing even exists I was reading a reddit post the other day where the guy lost his crypto holdings because he input his recovery phrase somewhere. We question the intelligence of LLMs because they might open a website, read something nefarious, and then do it. But here we have real humans doing the exact same thing... > I guess humans really aren't so special after all No they…

> But here we have real humans doing the exact same thing... I'd wager that a motivation in designing these systems it so they do not make these mistakes. Otherwise what's the point, really.

I think a system too perfect will not show any creativity. Maybe wild new ideas require taking risks which means a system that can invent new things will end up making bad choices.

Re: Chomsky on what ChatGPT is good for (2023)

#284

Earlier quoted context omitted.

A “complex” cfg is still a cfg, and, giving credence to Chomsky’s hierarchy, remains computationally less complex than natural, context sensitive, grammars. Even a complex cfg can be parsed by a relatively simple program in ways that context-sensitive grammars cannot. My understanding is that context sensitive grammars _can_ allow for recursive structures that are beyond cfgs, which is precisely why they sit below cs…

I don't think it's clear that human languages are context sensitive. The only consistent claim I can find is that at one point someone examined Swiss German and found that it's weakly context sensitive. Also empirically human language don't have that much recursion. You can artificially construct such examples, but beyond a certain depth people won't be able to parse it either. I don't know whether the non-existence…

It’s uncontroversial now that the class of string languages roughly corresponding to “human languages” is mildly context sensitive in a particular sense. This debate was hashed out in the 80s and 90s.

I don’t think formal languages classes have much to tell us about the capabilities of LLMs in any case.

>Also empirically human language don't have that much recursion. You can artificially construct such examples, but beyond a certain depth people won't be able to parse it either.

If you limit recursion depth then everything is regular, so the Chomsky hierarchy is of little application.

Re: Chomsky on what ChatGPT is good for (2023)

#285

There was an interesting debate where Chomsky took a position on intelligence being rooted in symbolic reasoning and Asimov asserted a statistical foundation (ah, that was not intentional ;). LLM designs to date are purely statistical models. A pile, a morass of floating point numbers and their weighted relationships, along with the software and hardware that animates them and the user input and output that makes the…

To me the interesting idea is the followup question: Can you do complex reasoning without intelligence? LLM's seem to have proven themselves to be more than a one-trick-pony. There is actually some resemblance of reasoning and structuring etc.. No matter if directly within the LLM, or supported by computer code. E.g it can be argued that the latest LLMs like Gemini 2.5 and Claude 4 in fact do complex reasoning. We ha…

> E.g it can be argued that the latest LLMs like Gemini 2.5 and Claude 4 in fact do complex reasoning.

They most definitely don't. We attach symbolic meaning to their output because we can map it semantically to the input we gave it. Which is why people are often caught by surprise when these mappings break down.

LLMs can emulate reasoning, but the failure modes show that they don't. We can get them to be coincidentally emulating reasoning well enough long enough to fools us, investors and the media. But doubling down on it hoping that this problem goes away with scale or fine tuning is proving more and more reckless.

Re: Chomsky on what ChatGPT is good for (2023)

#286
Brains don't have innate grammar more than languages are selected to fit baby brains. Chomsky got it backwards, languages co-evolved with human brains to fit our capacities and needs. If a language is not useful or can't be learned by children, it does not expand, it just disappears.

It's like wondering how well your shoes fit your feet, forgetting that shoes are made and chosen to fit your feet in the first place.

Re: Chomsky on what ChatGPT is good for (2023)

#287

There was an interesting debate where Chomsky took a position on intelligence being rooted in symbolic reasoning and Asimov asserted a statistical foundation (ah, that was not intentional ;). LLM designs to date are purely statistical models. A pile, a morass of floating point numbers and their weighted relationships, along with the software and hardware that animates them and the user input and output that makes the…

>There was an interesting debate where Chomsky took a position on intelligence being rooted in symbolic reasoning and Asimov asserted a statistical foundation (ah, that was not intentional ;).

Chomsky vs Norvig

https://norvig.com/chomsky.html

Re: Chomsky on what ChatGPT is good for (2023)

#288
post #280

Earlier quoted context omitted.

> AI this decade have not, at least so far, substantially deepened our understanding of our own intelligence and its constitution I would push back on this a little bit. While it has not helped us to understand our own intelligence, it has made me question whether such a thing even exists. Perhaps there are no simple and beautiful natural laws, like those that exists in Physics, that can explain how humans think and…

I think it is important to realize, that we need to understand language on our own terms. The logic of LLMs is not unlike alien technology to us. That being said, the minimalist program of Chomsky lead to nowhere, because just like programming, it found edge case after edge case, reducing it further and further, until there was no program anymore that resembled a real theory. But it is wrong to assume that the big pr…

I agree with you. I think the fundamental problem is we don't have a good unified theory of fuzzy reasoning. We have a lot of different formal approaches but they all have flaws.

Now LLMs made a big breakthrough that they showed we can do decent fuzzy reasoning in practice. But at the cost of nobody understanding the underlying process formally.

If we had a good unified (formal) theory of fuzzy reasoning, we could build models that reason better (or at least more predictably). But we won't get a better theory by scaling the existing models, I think Chomsky is right about that.

We lack the goal, not the means. If I am asking LLM a question, what answer do I want? A playfully creative one? A strictly logical one? A pleasingly sycophantic one? A harshly critical one? An out of the box devil's advocate one? A beautiful one? A practical one? We have no clue how to express these modes in logical reasoning.

Re: Chomsky on what ChatGPT is good for (2023)

#289
post #35

Chomsky’s notion is: LLMs can only imitate, not understand language. But what exactly is understanding? What if our „understanding“ is just unlocking another level in a model? Unlocking a new form of generation?

Actually no. Chomsky has never really given a stuff about Chinese Room style arguments about whether computers can “really” understand language. His problem with LLMs (if they are presented as a contribution to linguistic science) is primarily that they don’t advance our understanding of the human capacity for language. The main reasons for this are that (i) they are able to learn languages that are very much unlike human languages and (ii) they require vastly more linguistic data than human children have access to.

Re: Chomsky on what ChatGPT is good for (2023)

#290
post #238

Chomsky's own words. https://www.nytimes.com/2023/03/08/opinion/noam-chomsky-chat...

Most likely not. This is one of his weird pieces co-authored with Jeffrey Watamull. I don’t doubt that he put his name on it voluntarily, but it reads much more like Watamull than Chomsky. The views expressed in the interview we’re commenting on are much more Chomsky-like.
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