I also agree GPT-4 isn’t AGI, but with a significant proviso: There appears to be research that could plausibly make an AGI with enough engineering, which if Nathan Helm-Burger is to be believed, could come really fast (specifically it allows an AI to act as a Universal Turing Machine because it has the tools necessary to solve arbitrarily long problems in it’s memory, and arbitrarily long or complicated problems could be solved this way.)
Here’s a edited quote from Nathan Helm-Burger on the research to create an AGI:
I have looked into this in my research and found some labs doing work which would enable this. So it’s more of a question of when the big labs will decide to take integrate these ideas developed by academic groups into SoTA models, not a question of whether it’s possible. There’s a lot of novel capabilities like this that have been demonstrated to be possible but not yet been integrated, even when trying to rule out those which might get blocked by poor scaling/parallelizability.
So, the remaining hurdles seem to be more about engineering solutions to integration challenges, rather than innovation and proof-of-concept.
Yeah, there are a ton of near term capabilities that are one paper away. The world ones IMO are the ones that add RL, or use LLM’s in RL. Since that would increase it’s agent-ness, and lead to RL like misalignment. And RL misalignment seems much worse than LLM misalignment at the present time.
I also agree GPT-4 isn’t AGI, but with a significant proviso: There appears to be research that could plausibly make an AGI with enough engineering, which if Nathan Helm-Burger is to be believed, could come really fast (specifically it allows an AI to act as a Universal Turing Machine because it has the tools necessary to solve arbitrarily long problems in it’s memory, and arbitrarily long or complicated problems could be solved this way.)
Here’s a edited quote from Nathan Helm-Burger on the research to create an AGI:
Yeah, there are a ton of near term capabilities that are one paper away. The world ones IMO are the ones that add RL, or use LLM’s in RL. Since that would increase it’s agent-ness, and lead to RL like misalignment. And RL misalignment seems much worse than LLM misalignment at the present time.