I've been wondering about something similar to you, but I read one of Pearl's causality books recently and thought that might be the missing piece.
It's certainly impressive what GPT-3 can do, but it boggles the mind how much data went into it. By contrast a well-educated renaissance man might have read a book every month or so from age 15 to 30? That doesn't seem to be anywhere near what GPT could swallow in a few seconds.
When you look at how GPT answers things, it kinda feels like someone who has heard the keywords and can spout some things that at least obscure whether it has ever studied a given subject, and this is impressive. What I wonder is whether it can do reasoning of the causality kind: what if X hadn't happened, what evidence do we need to collect to know if theory Z is falsified, which data W is confounding?
To me it seems that sort of thing is what smart people are able to work out, with a lot of reading, but not quite the mountain that GPT reads.
It's certainly impressive what GPT-3 can do, but it boggles the mind how much data went into it. By contrast a well-educated renaissance man might have read a book every month or so from age 15 to 30? That doesn't seem to be anywhere near what GPT could swallow in a few seconds.
When you look at how GPT answers things, it kinda feels like someone who has heard the keywords and can spout some things that at least obscure whether it has ever studied a given subject, and this is impressive. What I wonder is whether it can do reasoning of the causality kind: what if X hadn't happened, what evidence do we need to collect to know if theory Z is falsified, which data W is confounding?
To me it seems that sort of thing is what smart people are able to work out, with a lot of reading, but not quite the mountain that GPT reads.