Of course 99.9% of humans also struggle with competitive programming. It seems to be an overly high bar for AGI if it has to compete with experts from every single field.
That said, GPT has no model of the world. It has no concept of how true the text it is generating is. Its going to be hard for me to think of that as AGI.
I don't think this is necessarily true. Here is an example where researchers trained a transformer to generate legal sequences of moves in the board game Othello. Then they demonstrated that the internal state of the model did, in fact, have a representation of the board.
I'm not sure, the reason you could prove for Othello that the 'world model' exists is that the state is so simple there is really only one reasonable way to represent it with a vector (one component for each square). Even for something like chess there is a huge amount of choice for how to represent the board, yet alone trying represent the state of the actual world.
Even the current GPT has models of the domains it was trained on. That is why it can solve unseen problems within those domains. What it lacks is the ability to generalize beyond the domains. (And I did not suggest it was an AGI.)
If an LLM can solve Codeforces problems as well as a strong competitor—-in my hypothetical future LLM—-what else can it not do as well as competent humans (aside from physical tasks)?
it's an overly high bar, but it seems well on its way to competing with experts from every field. it's terrifying.
and I'm not so sure it has no model of the world. a textual model, sure, but considering it can recognize what svgs are pictures of from the coordinates alone, that's not much of a limitation maybe.
That said, GPT has no model of the world. It has no concept of how true the text it is generating is. Its going to be hard for me to think of that as AGI.