Interesting, I find what you are saying here broadly plausible, and it is updating me (at least toward greater uncertainity/confusion). I notice that I don’t expect the 10x effect, or the Von Neumann effect, to be anywhere close to purely genetic. Maybe some path-dependency in learning? But my intuition (of unknown quality) is that there should be some software tweaks which make the high end of this more reliably achievable.
Anyway, to check that I understand your position, would this be a fair dialogue?:
Person: “The jump from chimps to humans is some combination of a 3x scaleup and some algorithmic improvements. Once you have human-level AI, scaling it up 3x and adding a chimp-to-human-jump worth of algorithmic improvement would get you something vastly superhuman, like 30x or 1000x Von Neumann, if not incomparable.”
Vivek’s model of Jacob: “Nope. The 3x scaleup is the only thing, there wasn’t much algorithmic improvement. The chimp-to-human scaling jump was important because it enabled language/accumulation, but there is nothing else left like that. There’s nothing practical you can do with 3x human-level compute that would 30x Von Neumann[1], even if you/AIs did a bunch of algorithmic research.”
I find your view more plausible than before, but don’t know what credence to put on it. I’d have more of a take if I properly read your posts.
Your model of my model sounds about right, but I also include neotany extension of perhaps 2x which is part of the scale up (spending longer on training the cortex, especially in higher brain regions).
For Von Neumann in particular my understanding is he was some combination of ‘regular’ genius and a mentant (a person who can perform certain computer like calculations quickly), which was very useful for many science tasks in an era lacking fast computers and software like mathematica, but would provide less of an effective edge today. It also inflated people’s perception of his actual abilities.
Interesting, I find what you are saying here broadly plausible, and it is updating me (at least toward greater uncertainity/confusion). I notice that I don’t expect the 10x effect, or the Von Neumann effect, to be anywhere close to purely genetic. Maybe some path-dependency in learning? But my intuition (of unknown quality) is that there should be some software tweaks which make the high end of this more reliably achievable.
Anyway, to check that I understand your position, would this be a fair dialogue?:
I find your view more plausible than before, but don’t know what credence to put on it. I’d have more of a take if I properly read your posts.
I’m not sure how to operationalize this “30x-ing” though. Some candidates:
- “1000 scientists + 30 Von Neumanns” vs. “1000 scientists + 1 ASI”
- “1 ASI” vs. “30 Von Neumanns”
- “100 ASIs” vs. “3000 Von Neumanns”
Your model of my model sounds about right, but I also include neotany extension of perhaps 2x which is part of the scale up (spending longer on training the cortex, especially in higher brain regions).
For Von Neumann in particular my understanding is he was some combination of ‘regular’ genius and a mentant (a person who can perform certain computer like calculations quickly), which was very useful for many science tasks in an era lacking fast computers and software like mathematica, but would provide less of an effective edge today. It also inflated people’s perception of his actual abilities.