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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)

#81
post #46

All this interview proves is that Chomsky has fallen far, far behind how AI systems work today and is retreating to scoff at all the progress machine learning has achieved. Machine learning has given rise to AI now. It can't explain itself from principles or its architecture. But you couldn't explain your brain from principles or its architecture, you'd need all of neuroscience to do it. Because the brain is digital…

> Not to mention all the "just engineering" of making chips crunch incredible amounts of numbers.

Are LLM's still the same black box as they were described as a couple years ago? Are their inner workings at least slightly better understood than in the past?

Running tens of thousands of chips crunching a bajillion numbers a second sounds fun, but that's not automatically "engineering". You can have the same chips crunching numbers with the same intensity just to run an algorithm to run a large prime number. Chips crunching numbers isn't automatically engineering IMO. More like a side effect of engineering? Or a tool you use to run the thing you built?

What happens when we build something that works, but we don't actually know how? We learn about it through trial and error, rather than foundational logic about the technology.

Sorta reminds me of the human brain, psychology, and how some people think psychology isn't science. The brain is a black box kind of like a LLM? Some people will think it's still science, others will have less respect.

This perspective might be off base. It's under the assumption that we all agree LLM's are a poorly understood black box and no one really knows how they truly work. I could be completely wrong on that, would love for someone else to weigh in.

Separately, I don't know the author, but agreed it reads more like a pop sci book. Although I only hope to write as coherently as that when I'm 96 y/o.

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

#84

Earlier quoted context omitted.

Tons of people fall for this too. Are they not reasoning? LLMs can also be bad reasoning machines.

I dont have much use for a bad reasoning machine.

I can think of tons of uses for a bad reasoning machine as long as it’s cheap enough.

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

#85
post #46

All this interview proves is that Chomsky has fallen far, far behind how AI systems work today and is retreating to scoff at all the progress machine learning has achieved. Machine learning has given rise to AI now. It can't explain itself from principles or its architecture. But you couldn't explain your brain from principles or its architecture, you'd need all of neuroscience to do it. Because the brain is digital…

Perhaps it should be mentioned that he is 96 years old.

Wow, he is, isn’t he. I hope I’m this coherent when I’m 96.

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

#86
"The desert ants in my backyard have minuscule brains, but far exceed human navigational capacities, in principle, not just performance. There is no Great Chain of Being with humans at the top."

This quote brought to mind the very different technological development path of the spider species in Adrian Tchaikovsky's Children of Time. They used pheromones to 'program' a race of ants to do computation.

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

#87

"Expert in (now-)ancient arts draws strange conclusion using questionable logic" is the most generous description I can muster. Quoting Chomsky: > These considerations bring up a minor problem with the current LLM enthusiasm: its total absurdity, as in the hypothetical cases where we recognize it at once. But there are much more serious problems than absurdity. > One is that the LLM systems are designed in such a way…

> LLMs do surface real linguistic structure...

It's completely irrelevant because the point he's making is that LLMs operate differently from human languages as evidenced by the fact that they can learn language structures that humans cannot learn. Put another way, I'm sure you can point out an infinitude of similarities between human language faculty and LLMs but it's the critical differences that make LLMs not useful models of human language ability.

> When you feed them “impossible” languages (e.g., mirror-order or random-agreement versions of English), perplexity explodes and structure heads disappear—evidence that the models do encode natural-language constraints.

This is confused. You can pre-train an LLM on English or an impossible language and they do equally well. On the other hand humans can't do that, ergo LLMs aren't useful models of human language because they lack this critical distinctive feature.

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

#88

[flagged]

From some Googling and use of Claude (and from summaries of the suggestively titled "Impossible Languages" by Moro linked from https://en.wikipedia.org/wiki/Universal_grammar ), it looks like he's referring to languages which violate the laws which constrain the languages humans are innately capable of learning. But it's very unclear why "machine M is capable of learning more complex languages than humans" implies an…

It doesn't, it just says that LLMs are not useful models of the human language faculty.

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

#89

It's amusing that he argues (correctly) that "there is no Great Chain of Being with humans at the top," but then claims that LLMs cannot tell us anything about language because they can learn "impossible languages" that infants cannot learn. Isn't that an anthropomorphic argument, saying that what a language is inherently defined by human cognition?

Yes, studying human language is actually inherently defined by what humans do, just -- as he points out, if you could understand the article -- studying insect navigation is defined by what insects do and not what navigation systems human could design.

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

#90
post #46

All this interview proves is that Chomsky has fallen far, far behind how AI systems work today and is retreating to scoff at all the progress machine learning has achieved. Machine learning has given rise to AI now. It can't explain itself from principles or its architecture. But you couldn't explain your brain from principles or its architecture, you'd need all of neuroscience to do it. Because the brain is digital…

"I think we should probably stop listening to Chomsky"

I've been saying this my whole life, glad it's finally catching on

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