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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)

#331

Post by namaria »

jamincan wrote: post #313
namaria wrote: post #285

Earlier quoted context omitted.

> 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 coincidenta…

Humans aren't infallible and make mistakes in reasoning as well. What is fundamentally different about the mistakes we make versus the mistakes that Claude or Gemini make? Haven't LLM's even been shown to make the same posthoc rationalizations of mistakes that we as humans do all the time?

Unless you're pulling humans out of the streets at random and asking them questions or to do work, I guess you also shouldn't do that with statistical models of random human language.

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

#332

Post by codr7 »

catigula wrote: post #194
codr7 wrote: post #193

Earlier quoted context omitted.

If they are, knowing what they potentially know about humans by now, they would probably do their best to hide it.

I don't think their experience of consciousness would be very analogous to what you and I understand.

I agree, but having spent 40 years interacting with computers I feel like I have a pretty good idea what they're up to/capable of.

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

#333

Post by numpad0 »

suddenlybananas wrote: post #319
thomassmith65 wrote: post #304

Earlier quoted context omitted.

The great breakthrough in AI turned out to be LLMs. Nature , for an LLM, is its design: graph, starting weights, etc. Environment , for an LLM, is what happens during training. LLMs are capable of learning grammar entirely from their environment, which suggests that infants are too, which is bad for Chomsky's position that the basics of grammar are baked into human DNA.

LLMs require vastly more data than humans and still struggle with some more esoteric grammatical rules like parasitic gaps. The fact grammar can be approximated given trillions of words doesn't explain how babies learn language from a much more modest dataset.

I think it does. I think LLM showed us possibility that maybe there's no language but just pile of memes and supplemental compression scheme that is grammar.

LLM had really destroyed Chomsky's positions in multiple different ways: nothing perform even close to LLM in language generation, yet it didn't grow a UG for natural languages, while it did develop a shared logic for non-natural languages and abstract concepts, while dataset needing to be heavily English biased to be English fluent, and parameter count needing to be truly massive as multiple hundred billion parameters large, so on and on.

Those are all circumstantial evidences at best, a random paraphernalia of statements that aren't even appropriate to bring into discussions, all meaningless - in the sense that an open hand of a person observing another individual aligned to a line between standing position of the person to the center of nearest opening of a wall would be meaningless.

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

#334

Post by Balgair »

loveparade wrote: post #201
atdt wrote: post #178

The level of intellectual engagement with Chomsky's ideas in the comments here is shockingly low. Surely, we are capable of holding these two thoughts: one, that the facility of LLMs is fantastic and useful, and two, that the major breakthroughs of AI this decade have not, at least so far, substantially deepened our understanding of our own intelligence and its constitution. That may change, particularly if the intel…

> 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…

Neuroscientist here:

> Perhaps there are no simple and beautiful natural laws, like those that exists in Physics, that can explain how humans think and make decisions...Perhaps it's all just emergent properties of some messy evolved substrate.

Yeah, it is very likely that there are not laws that will do this, it's the substrate. The fruit fly brain (let alone human) has been mapped, and we've figured out that it's not just the synapse count, but the 'weights' that matter too [0]. Mind you, those weights adjust in real time when a living animal is out there.

You'll see in literature that there are people with some 'lucky' form of hydranencephaly where their brain is as thin as paper. But they vote, get married, have kids, and for some strange reason seem to work in mailrooms (not a joke). So we know it's something about the connectome that's the 'magic' of a human.

My pet theory: We need memristors [2] to better represent things. But that takes redesigning the computer from the metal on up, so is unlikely to occur any time soon with this current AI craze.

> 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" which is similar to what we've been through with Physics.

Yeah, biologists get there too, just the other way abouts, with animals and humans. Like, dogs make vitamin C internally, and humans have that gene too, it's just dormant, ready for evolution (or genetic engineering) to reactivate. That said, these neuroscience issues with us and the other great apes are somewhat large and strange. I'm not big into that literature, but from what little I know, the exact mechanisms and processes that get you from tool using ourangs to tool using humans, well, those seem to be a bit strange and harder to grasp for us. Again, not in that field though.

In the end though, humans are special. We're the only ones on the planet that ever really asked a question. There's a lot to us and we're actually pretty strange in the end. There's many centuries of work to do with biology, we're just at the wading stage of that ocean.

[0] https://en.wikipedia.org/wiki/Drosophila_connectome

[1] https://en.wikipedia.org/wiki/Hydranencephaly

[2] https://en.wikipedia.org/wiki/Memristor

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

#335

Post by catigula »

codr7 wrote: post #332
catigula wrote: post #194

Earlier quoted context omitted.

I don't think their experience of consciousness would be very analogous to what you and I understand.

I agree, but having spent 40 years interacting with computers I feel like I have a pretty good idea what they're up to/capable of.

Sure, but you still have no idea what consciousness is.

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

#336

Post by [deleted] »

guappa wrote: post #279
dghlsakjg wrote: post #33

Earlier quoted context omitted.

Isn’t that just a Turing test? I’m perfectly willing to bet that there are LLMs that can pass a Turing test, even against a mind like Chomsky.

Just ask for an opinion on who's right between israel and palestine and an AI will refuse to reply :D

[deleted]

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

#337

Post by r00sty »

I imagine his opinions might have changed by now. If we're still residing in 2023, I would be inclined to agree with him. Today, in 2025 however, LLMs are just another tool being used to "reduce labor costs" and extract more profit from the humans left who have money. There will be no scientific developments if things continue in this manner.

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

#338

Post by CamperBob2 »

hyperadvanced wrote: post #235
Workaccount2 wrote: post #213

Earlier quoted context omitted.

99.9% of humans will never solve a novel problem. It's a bad benchmark to use here

I agree. But it’s worth being somewhat skeptical of ASI scenarios if you can’t, for example, give a well formulated math problem to a LLM and it cannot solve it. Until we get a Reimann hypothesis calculator (or equivalent for hard/old unsolved maths) it’s kind of silly to be debating the extreme ends of AI cognition theory

"I'm taking this talking dog right back to the pound. It completely whiffed on both Riemann and Goldbach. And you should see the buffer overflows in the C++ code it wrote for me."

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

#339

Post by suddenlybananas »

thomassmith65 wrote: post #330
suddenlybananas wrote: post #328

Earlier quoted context omitted.

That's not the goal of generative linguistics though; it's not an engineering project.

The problem encompasses not just biology and information technology, but also linguistics. Even if LLMs say nothing about biology, they do tell us something about the nature of language itself. Again, that LLMs can learn to compose sophisticated texts from training alone does not close the case on Chomsky's position. However, it is a piece of evidence against it. It does suggest, by Occam's razor, that a hardwired un…

How do LLMs explain how 5 year olds respect island constraints?

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

#340

Post by suddenlybananas »

numpad0 wrote: post #333
suddenlybananas wrote: post #319

Earlier quoted context omitted.

LLMs require vastly more data than humans and still struggle with some more esoteric grammatical rules like parasitic gaps. The fact grammar can be approximated given trillions of words doesn't explain how babies learn language from a much more modest dataset.

I think it does. I think LLM showed us possibility that maybe there's no language but just pile of memes and supplemental compression scheme that is grammar. LLM had really destroyed Chomsky's positions in multiple different ways: nothing perform even close to LLM in language generation, yet it didn't grow a UG for natural languages, while it did develop a shared logic for non-natural languages and abstract concepts,…

>LLM had really destroyed Chomsky's positions in multiple different ways: nothing perform even close to LLM in language generation, yet it didn't grow a UG for natural languages

Do you even understand Chomsky's position?

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