I have been thinking for a few weeks now that we need another term for large language models trained on colossal datasets: AGK, artificially generally/globally knowledgeable. It can mimic a likeness of problem solving because the corpus it was trained on is full of problem/solution pairs in the abstract. But task it with any novel problem solving challenge outside of its training that is of sufficient complexity and it will balk, thereby precluding it from being AGI, because humans are by nature problem solvers.

Furthermore, I just don’t feel like the transformer architecture is suited for problem solving. Like I may just be a charlatan but self attention over the space of words does not seem like it’s going to be enough, and praying it falls out in emergent behavior if we can just add more parameters is… unscientific-ish? Now, if you could figure out a way to do self-attention over the space of concepts? Maybe you’ve got something.

I feel like AlphaGo ideas and some variation on MCTS is more likely to produce a solid problem solving architecture.