Eh, it's certainly true that we're throwing tremendously more hardware and power at the problem with an LLM than with a toddler; that's only relevant to whether LLMs refute Chomsky to whatever degree his argument relied on hardware or power consumption (explicitly or implicitly) and my impression is that it didn't.
Wait so then what is his argument? Because you can always postulate that a large enough computer can simulate every human and therefore can learn stuff too — thus you don’t need a human to learn language, nyeh!
Obviously, all that stuff ChatGPT says about feelings and emotions came from humans writing it!
As I understand it, the question was whether humans learn language starting from a "blank slate" or whether there's some meaningful structure built in (that's therefore common across all human languages). Chomsky's argument was that children are not exposed to enough example sentences to learn all the rules they learn. It's an argument from the information content of the corpus made available to the language learner, irrespective of the capabilities of the learner.
Therefore, if we're able to do the same thing by simply applying more resources, that would undermine his argument in a way that doing the same thing with a vastly larger corpus (whatever the resources we throw at it) doesn't.
I should note that this is based on recollections from 20+ years ago and no serious engagement with the article at hand, so, uh, appropriate salt.
That makes no sense. A “vastly larger corpus” would not have the property of “not being exposed to enough example sentences”. If anything, the amount of sentences is far far more than any human would ever encounter — let alone a child.
Right, that's the point - success with a huge corpus doesn't tell us it would have been possible with a realistic corpus, so doesn't refute the argument.
