I think your point is that all these models are still somewhat specialized. At the same time, it appears that the transformer architecture works well with images, short video and text at the same time in the Flamingo model. And gato can perform 600 tasks while being a very small proof of concept. It appears to me that there is no reason to believe that it won't just scale to every task that you give it data for if it has enough parameters and compute.
[1]https://en.wikipedia.org/wiki/ELIZA_effect [2]https://www.economist.com/by-invitation/2022/06/09/artificia... Note: There's a critique of the article here but if you look at Radford Neal's comment, the point that GPT-3 is a clever lookup tool remains. https://www.greaterwrong.com/posts/ADwayvunaJqBLzawa/contra-...
Flatworms first appeared 800+ million years ago, while mouse lineage diverged from humans only 70-80 million years ago. If our AGI development timeline roughly follows the proportion it took natural evolution, it might be much too late to begin seriously thinking about AGI alignment when we get to mouse-level intelligence. Not to mention that no one knows how long it would take to really understand AGI alignment (much less implementing it in a practical system).
To be more concrete, in what aspects do you think latest models are inferior at generalizing than flatworms or mice, when less known work like “Emergent Tool Use from Multi-Agent Interaction” is also taken into account https://openai.com/blog/emergent-tool-use/?
> Flatworms first appeared 800+ million years ago
Surviving for 800 million years seems to me like a pretty good indicator of meaningful generalisation.
Our concern is not the survivability or adaptability over evolutionary timescale but the capabilities to affect the world in human timescale.