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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)

#261
post #239
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…

> the major breakthroughs of AI this decade have not, at least so far, substantially deepened our understanding of our own intelligence and its constitution People's illusions and willingness to debase their own authority and control to take shortcuts to optimise towards lowest effort / highest yield (not dissimilar to something you would get with... auto regressive models!) was an astonishing insight to me.

Well said. It's wild when you think of how many "AI" products are out there that essentially entrust an LLM to make the decisions the user would otherwise make. Recruitment, trading, content creation, investment advice, medical diagnosis, legal review, dating matches, financial planning and even hiring decisions.

At some point you have to wonder: is an LLM making your hiring decision really better than rolling a dice? At least the dice doesn't give you the illusion of rationality, it doesn't generate a neat sounding paragraph "explaining" why candidate A is the obvious choice. The LLM produces content that looks like reasoning but has no actual causal connection to the decision - it's a mimicry of explanation without true substance of causation.

You can argue that humans do the same thing. But post-hoc reasoning is often a feedback loop for the eventual answer. That's not the case for LLMs.

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

#262

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…

> and very appealing to us

Yes, because anthropomorphism is hardwired into our biology. Just two dots and an arc triggers a happy feeling in all humans. :)

> of practical application and real value

That is debatable. So far no groundbreaking useful applications have been found for LLMs. We want to believe, because they make us feel happy. But the results aren't there.

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

#263

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.

Its like saying:

Ah, but these wizards created a magical entity that can also do magic! Wizards must not be so special after all...

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

#264
post #99

The fact that we have figured out how to translate language into something a computer can "understand" should thrill linguists. Taking a word (token) and abstracting it's "meaning" as a 1,000-dimension vector seems like something that should revolutionize the field of linguistics. A whole new tool for analyzing and understanding the underlying patterns of all language! And there's a fact here that's very hard to disp…

Restricted to linguistics, LLM's supposed lack of understanding should be a non-sequitur. If the question is whether LLMs have formed a coherent ability to parse human languages, the answer is obviously yes. In fact not just human languages, as seen with multimodality the same transformer architecture seems to work well to model and generate anything with inherent structure. I'm surprised that he doesn't mention "uni…

> If the question is whether LLMs have formed a coherent ability to parse human languages, the answer is obviously yes.

No, not "obviously". They work well for languages like English or Chinese, where word order determines grammar.

They work less well where context is more important. (e.g. Grammatical gender consistency.)

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

#266
post #99

The fact that we have figured out how to translate language into something a computer can "understand" should thrill linguists. Taking a word (token) and abstracting it's "meaning" as a 1,000-dimension vector seems like something that should revolutionize the field of linguistics. A whole new tool for analyzing and understanding the underlying patterns of all language! And there's a fact here that's very hard to disp…

"The fact that we have figured out how to translate language into something a computer can "understand" should thrill linguists." No, there is no understanding at all. Please don't confuse codifying with understanding or translation. LLMs don't understand their input, they simply act on it based on the way they are trained on it. "And there's a fact here that's very hard to dispute, this method works. I can give a co…

I think the overarching theme that I glean from LLM critics is some kind of visceral emotional reaction, disgust even, with the idea of them, leading to all these proxy arguments and side quests in order to try and denigrate the idea of them without actually honestly engaging with what they are or why people are interacting with them.

so what they don't "understand", by your very specific definition of the word "understanding"? the person you're replying to is talking about the fact that they can say something to their computer in the form of casual human language and it will produce a useful response, where previously that was not true. whether that fits your suspiciously specific definition of "understanding" does not matter a bit.

so what they are over-confident with areas outside of their training data? provide more training data, improve the models, reduce the hallucination. it isn't an issue with the concept, it's an issue with the execution. yes you'll never be able to reduce it to 0%, but so what? humans hallucinate too. what are we aiming for? omniscience?

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

#267
post #177

Earlier quoted context omitted.

An LLM will get ... what exactly ? The ability to reorder its sentences ? The LLM doesn't think, doesn't understand, doesn't know what matters more than not, doesn't use what it learns, doesn't expand what it learns to new knowledge, doesn't enjoy reading that book and doesn't suffer through it. So what is it really gonna do with a book, that LLM ? Reorder its internal matrix to be a little bit more precise when auto…

LLM models are to a large extent neuronal analogs of human neural architecture - of course they reason The claim of the “stochastic parrot” needs to go away Eg see: https://www.anthropic.com/news/golden-gate-claude I think the rub is that people think you need consciousness to do reasoning, I’m NOT claiming LLMs have consciousness or awareness

> LLM models are to a large extent neuronal analogs of human neural architecture

They are absolutely not. Despite the disingenuous name, computer neural nets are nothing like biological brains.

(Neural nets are a generalization of the logistic regression.)

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

#268

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 have always taken for granted you need intelligence for that, but what if you don't? It would greatly change our view on intelligence and take away one of the main factors that we test for in e.g. animals to define their "intelligence".

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

#269
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…

It indeed baffles me how academics overall seem so dismissive of recent breakthroughs in sub-symbolic approaches as models from which we can learn about 'intelligence'?

It is as if a biochemist looks at a human brain, and concludes there is no 'intelligence' there at all, just a whole lot of electro-chemical reactions. It fully ignores the potential for emergence.

Don't misunderstand me, I'm not saying 'AGI has arrived', but I'd say even current LLM's do most certainly have interesting lessons for Human Language development and evolution in science. What can the success in transfer learning in these models contribute to the debates on universal language faculties? How do invariants correlated across LLM systems and humans?

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

#270

I'm noticing that leftists overwhelmingly toe the same line on AI skepticism, which suggests to me an ideological motivation.

Chomsky's problem here has nothing to do with his politics, but unfortunately a lot to do with his long-held position in the Nature/Nurture debate - a position that is undermined by the ability of LLMs to learn language without hardcoded grammatical rules: Chomsky introduced his theory of language acquisition, according to which children have an inborn quality of being biologically encoded with a universal grammar ht…

I don't see how the two things are related. Whether acquisition of human language is nature or nurture - it is still learning of some sort.

Yes, maybe we can reproduce that learning process in LLMs, but that doesn't mean the LLMs imitate only the nurture part (might as well be just finetuning), and not the nature part.

An airplane is not an explanation for a bird's flight.

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