I agree that it can’t be a vaild model of AI timelines, because it essentially assumes the conclusion that we already have (distributed) TAI/AGI in the assumption that more output implies more people, which implies more output, leading to hyperbolic growth.
More generally, I agree that there are some fatal flaws to using the model as a timelines forecast, and this is enough to make it not useful as a prediction of timelines.
But I do think it’s a much better model of takeoff after AGI assuming no software-only singularity than it is a timelines forecast, and I think the most important part of the conclusion here is that not believing in a software-only singularity is not enough to defeat the general conclusion of a singularity happening once we can create workers purely from compute/capital (this also holds for automation based on data, too, see this paper or this tweet)
Fourth, long-run growth: data and capital (compute) accumulation feed into each other. Data simultaneously augments task-specific productivity + gradually shrinks need for labor ⇒ learning-by-doing singularity (infinite growth in finite time!) But this happens pretty slowly vs ‘software only singularities’ (@TomDavidsonX@BasilHalperin Tom H @akorinek)
These views aren’t mutually exclusive! In a way we’re being pretty conservative – the economy is messy, but we know how to do RL so this data channel is lower bound on how crazy things can get! Basil and I think it’s worth unifying both views and taking it to data!
And many economists dispute this conclusion given the assumption, so it is worth it to make them learn about this model or other models like Damon Binder’s model on how fast growth could be assuming robots + AGI but no software-only singularity (short version we could go from doubling the economy in 20 years for advanced economies to doubling it in a year, and with only known tech, could double the economy in a month after economic optimization.)
I think one of the bigger reasons economists haven’t considered this possibility is because they pattern-match AI to the technologies of the last 100-200 years, which only created/sustained exponential growth, and as it turned out there was a slowdown in growth rates from 200,000 BCE to 1880 AD, but the better model here is like creating new people, which over the long-term has increased growth superexponentially, and here the deep history of the last 200,000 years is more relevant.
I agree that it can’t be a vaild model of AI timelines, because it essentially assumes the conclusion that we already have (distributed) TAI/AGI in the assumption that more output implies more people, which implies more output, leading to hyperbolic growth.
More generally, I agree that there are some fatal flaws to using the model as a timelines forecast, and this is enough to make it not useful as a prediction of timelines.
But I do think it’s a much better model of takeoff after AGI assuming no software-only singularity than it is a timelines forecast, and I think the most important part of the conclusion here is that not believing in a software-only singularity is not enough to defeat the general conclusion of a singularity happening once we can create workers purely from compute/capital (this also holds for automation based on data, too, see this paper or this tweet)
And many economists dispute this conclusion given the assumption, so it is worth it to make them learn about this model or other models like Damon Binder’s model on how fast growth could be assuming robots + AGI but no software-only singularity (short version we could go from doubling the economy in 20 years for advanced economies to doubling it in a year, and with only known tech, could double the economy in a month after economic optimization.)
I think one of the bigger reasons economists haven’t considered this possibility is because they pattern-match AI to the technologies of the last 100-200 years, which only created/sustained exponential growth, and as it turned out there was a slowdown in growth rates from 200,000 BCE to 1880 AD, but the better model here is like creating new people, which over the long-term has increased growth superexponentially, and here the deep history of the last 200,000 years is more relevant.