10 million times faster is really a lot—on modern hardware, running SOTA object segmentation models at even 60fps is quite hard, and those are usually much much smaller than the kinds of AIs we would think about in the context of AI risk.
But − 100x faster is totally plausible (especially w/100x the energy consumption!) - and I think the argument still mostly works at that much more conservative speedup.
it’s completely implausible they’d run their entire processing system 10 million times faster, yeah. running a full brain costs heat, and that heat has to dissipate, there aren’t speed shortcuts.
our fastest neurons are on order 1000 hz, and our median neurons are on order 1hz. it’s the fast paths through the network that affect fastest reasoning. the question, then, is how much a learning system can distill its most time-sensitive reasoning into the fast paths. eg, self-directed distillation of a skill into an accelerated network that calls out to the slower one.
there’s no need for a being to run their entire brain at speed. being able to generate a program to run at 1ghz that can outsmart a human’s motor control is not difficult—flies are able to outsmart our motor control by running at a higher frequency despite being much smaller than us in every single way. this is the video I would link to show how much frequency matters: https://www.youtube.com/watch?v=Gvg242U2YfQ
10 million times faster is really a lot—on modern hardware, running SOTA object segmentation models at even 60fps is quite hard, and those are usually much much smaller than the kinds of AIs we would think about in the context of AI risk.
But − 100x faster is totally plausible (especially w/100x the energy consumption!) - and I think the argument still mostly works at that much more conservative speedup.
it’s completely implausible they’d run their entire processing system 10 million times faster, yeah. running a full brain costs heat, and that heat has to dissipate, there aren’t speed shortcuts.
our fastest neurons are on order 1000 hz, and our median neurons are on order 1hz. it’s the fast paths through the network that affect fastest reasoning. the question, then, is how much a learning system can distill its most time-sensitive reasoning into the fast paths. eg, self-directed distillation of a skill into an accelerated network that calls out to the slower one.
there’s no need for a being to run their entire brain at speed. being able to generate a program to run at 1ghz that can outsmart a human’s motor control is not difficult—flies are able to outsmart our motor control by running at a higher frequency despite being much smaller than us in every single way. this is the video I would link to show how much frequency matters: https://www.youtube.com/watch?v=Gvg242U2YfQ