Given the premises, I guess I’m willing to grant that this isn’t a silly extrapolation, and absent them it seems like you basically agree with the post?
However, I have a few notes on why I’d reject your premises.
On your first idea, I think high-fidelity biology simulators require so much understanding of biology that they are subsequent to ASI, rather than a replacement. And even then, you’re still trying to find something by searching an exponential design space—which is nontrivial even for AGI with feasible amounts of “unlimited” compute. Not only that, but the thing you’re looking for needs to do a bunch of stuff that probably isn’t feasible due to fundamental barriers (Not identical to the ones listed there, but closely related to them.)
On your second idea, a software-only singularity assumes that there is a giant compute overhang for some specific buildable general AI that doesn’t even require specialized hardware. Maybe so, but I’m skeptical; the brain can’t be simulated directly via Deep NNs, which is what current hardware is optimized for. And if some other hardware architecture using currently feasible levels of compute is devised, there still needs to be a massive build-out of these new chips—which then allows “enough compute has been manufactured that nanotech-level things can be developed.” But that means you again assume that arbitrary nanotech is feasible, which could be true, but as the other link notes, certainly isn’t anything like obvious.
(It’s useful to clearly distinguish exploration of what follows from some premises, and views on whether the premises are important/likely/feasible. Issues with the latter are no reason at all to hesitate or hedge with the former.)
But that means you again assume that arbitrary nanotech is feasible, which could be true, but as the other link notes, certainly isn’t anything like obvious.
I mentioned arbitrary nanotech, but it’s not doing any work there as an assumption. So it being infeasible doesn’t change the point about macroscopic biotech possibly being first, which is technically still the case if nanotech doesn’t follow at all.
Various claims that nanotech isn’t feasible are indeed the major reason I thought about this macroscopic biotech thing, since existing biology is a proof of concept, so some of the arguments against feasibility of nanotech clearly don’t transfer. It still needs to be designed, and the difficulty of that is unclear, but there seem to be fewer reasons to suspect it’s not feasible (at a given level of capabilities).
The macroscopic biotech that accomplishes what you’re positing is addressed in the first part, and the earlier comment where I note that you’re assuming ASI level understanding of bio for exploring an exponential design space for something that isn’t guaranteed to be possible. The difficulty isn’t unclear, it’s understood not to bebfeasible.
Given the premises, I guess I’m willing to grant that this isn’t a silly extrapolation, and absent them it seems like you basically agree with the post?
However, I have a few notes on why I’d reject your premises.
On your first idea, I think high-fidelity biology simulators require so much understanding of biology that they are subsequent to ASI, rather than a replacement. And even then, you’re still trying to find something by searching an exponential design space—which is nontrivial even for AGI with feasible amounts of “unlimited” compute. Not only that, but the thing you’re looking for needs to do a bunch of stuff that probably isn’t feasible due to fundamental barriers (Not identical to the ones listed there, but closely related to them.)
On your second idea, a software-only singularity assumes that there is a giant compute overhang for some specific buildable general AI that doesn’t even require specialized hardware. Maybe so, but I’m skeptical; the brain can’t be simulated directly via Deep NNs, which is what current hardware is optimized for. And if some other hardware architecture using currently feasible levels of compute is devised, there still needs to be a massive build-out of these new chips—which then allows “enough compute has been manufactured that nanotech-level things can be developed.” But that means you again assume that arbitrary nanotech is feasible, which could be true, but as the other link notes, certainly isn’t anything like obvious.
(It’s useful to clearly distinguish exploration of what follows from some premises, and views on whether the premises are important/likely/feasible. Issues with the latter are no reason at all to hesitate or hedge with the former.)
I mentioned arbitrary nanotech, but it’s not doing any work there as an assumption. So it being infeasible doesn’t change the point about macroscopic biotech possibly being first, which is technically still the case if nanotech doesn’t follow at all.
Various claims that nanotech isn’t feasible are indeed the major reason I thought about this macroscopic biotech thing, since existing biology is a proof of concept, so some of the arguments against feasibility of nanotech clearly don’t transfer. It still needs to be designed, and the difficulty of that is unclear, but there seem to be fewer reasons to suspect it’s not feasible (at a given level of capabilities).
The macroscopic biotech that accomplishes what you’re positing is addressed in the first part, and the earlier comment where I note that you’re assuming ASI level understanding of bio for exploring an exponential design space for something that isn’t guaranteed to be possible. The difficulty isn’t unclear, it’s understood not to bebfeasible.