Another reason I’d support reprogenetics work is because it might resolve one of the most burning questions in our minds, which is whether something like a software-only intelligence explosion is plausible, because there’s one (very major) constraint that applies to human intelligence augmentation that doesn’t apply to AI development, and that is the fact that we can’t increase computational power directly like we can for AI models by even 1 order of magnitude for inference or training, because we’d cook the body (at least not without technologies that is only practical to invent post-industrial explosion.)
This means work on reprogenetics could in theory probe the question indirectly, by measuring how large the returns to algorithmic progress are from a fixed base like the human mind.
We’d need much better measurements, especially measurements about whether or not when diminishing returns to intelligence without compute increases kicks in, and measurements about how well intelligence increases translate to other good metrics, but if we had the correct measurements, we could answer the question of whether software-only intelligence explosions are plausible, and to a first approximation, good AI policies (that aren’t just pure transparency/obviously good stuff) and good AI safety prioritization depend on answering this question.
Another reason I’d support reprogenetics work is because it might resolve one of the most burning questions in our minds, which is whether something like a software-only intelligence explosion is plausible, because there’s one (very major) constraint that applies to human intelligence augmentation that doesn’t apply to AI development, and that is the fact that we can’t increase computational power directly like we can for AI models by even 1 order of magnitude for inference or training, because we’d cook the body (at least not without technologies that is only practical to invent post-industrial explosion.)
This means work on reprogenetics could in theory probe the question indirectly, by measuring how large the returns to algorithmic progress are from a fixed base like the human mind.
We’d need much better measurements, especially measurements about whether or not when diminishing returns to intelligence without compute increases kicks in, and measurements about how well intelligence increases translate to other good metrics, but if we had the correct measurements, we could answer the question of whether software-only intelligence explosions are plausible, and to a first approximation, good AI policies (that aren’t just pure transparency/obviously good stuff) and good AI safety prioritization depend on answering this question.