Earlier quoted context omitted.
GPQA scores are mostly from pre-training, against content in the corpus. They have gone silent but look at the GPT4 technical report which calls this out. We are nowhere close to what Sam Altman calls AGI and transformers are still limited to what uniform-TC0 can do. As an example the Boolean Formula Value Problem is NC1-complete, thus beyond transformers but trivial to solve with a TM. As it is now proven that the f…
Isn't any physically realizable computer (including our brains) limited to what uniform-TC0 can do?
I wouldn't describe a computer's usual behavior as having constant depth.
It is fairly typical to talk about problems in P as being feasible (though when the constant factors are too big, this isn't strictly true of course).
Just because for unreasonably large inputs, my computer can't run a particular program and produce the correct answer for that input, due to my computer running out of memory, we don't generally say that my computer is fundamentally incapable of executing that algorithm.