(I’m not sure about this, thinking aloud; you may be right.)
AI is hard to regulate because
It’s hard to understand what it is, hence hard to point at it, hence hard to enforce bans. For nuclear stuff, you need lumps of stuff dug out of mines that can be detected by waving a little device over it. For bio, you have to have, like, big expensive machines? If you’re not just banning GPUs, what are you banning? Banning certain kinds of organizations is banning branding, and it doesn’t seem that hard to do AGI research with different branding that still works for recruitment. (This is me a little bit changing my mind; I think I agree that a ban could cause a temporary slowdown by breaking up conspicuous AGI research orgs, like DM or whatnot, but I think it’s not that much of a slowdown.) How could you ban compute? Could you ban having large clusters? What about networked piece-meal compute? How much slower would the latter be?
It looks like the next big superweapon. Nuclear plants are regulated, but before that, and after we knew what nuclear weapons meant, there was an arms race and thousands of nukes made. This hasn’t as much happened for biotech? The ban on chemical / bio weapons basically worked?
Its inputs are ubiquitous. You can’t order a gene synthesis machine for a couple hundred bucks with <week shipping, you can’t order a pile of uranium, but you can order GPUs, on your own, as much as you want. Compute is fungible, easy to store, cheap, safe (until it’s not), robust, and has a thriving multifarious economy supporting its production and R&D.
It’s highly shareable. You can’t stop the signal, so you can’t stop source code, tools, and ideas from being shared. (Which is a good thing, except for AGI...) And there’s a fairly strong culture of sharing in AI.
It’s highly scalable. Source code can be copied and run wherever, whenever, by whoever, and to some lesser extent also ideas. Costly inputs more temper the scalability of nuclear and bio stuff.
Prerequisite knowledge is privately, individually accessible. It’s easy to, on your own without anyone knowing, get a laptop and start learning to program, learning to program AI, and learning to experiment with AI. If you’re super talented, people might pay you to do this! I would guess that this is a lot less true with nuclear and bio stuff?
There’s lots of easily externally checkable benchmarks and test applications to notice progress.
(I’m not sure about this, thinking aloud; you may be right.)
AI is hard to regulate because
It’s hard to understand what it is, hence hard to point at it, hence hard to enforce bans. For nuclear stuff, you need lumps of stuff dug out of mines that can be detected by waving a little device over it. For bio, you have to have, like, big expensive machines? If you’re not just banning GPUs, what are you banning? Banning certain kinds of organizations is banning branding, and it doesn’t seem that hard to do AGI research with different branding that still works for recruitment. (This is me a little bit changing my mind; I think I agree that a ban could cause a temporary slowdown by breaking up conspicuous AGI research orgs, like DM or whatnot, but I think it’s not that much of a slowdown.) How could you ban compute? Could you ban having large clusters? What about networked piece-meal compute? How much slower would the latter be?
It looks like the next big superweapon. Nuclear plants are regulated, but before that, and after we knew what nuclear weapons meant, there was an arms race and thousands of nukes made. This hasn’t as much happened for biotech? The ban on chemical / bio weapons basically worked?
Its inputs are ubiquitous. You can’t order a gene synthesis machine for a couple hundred bucks with <week shipping, you can’t order a pile of uranium, but you can order GPUs, on your own, as much as you want. Compute is fungible, easy to store, cheap, safe (until it’s not), robust, and has a thriving multifarious economy supporting its production and R&D.
It’s highly shareable. You can’t stop the signal, so you can’t stop source code, tools, and ideas from being shared. (Which is a good thing, except for AGI...) And there’s a fairly strong culture of sharing in AI.
It’s highly scalable. Source code can be copied and run wherever, whenever, by whoever, and to some lesser extent also ideas. Costly inputs more temper the scalability of nuclear and bio stuff.
Prerequisite knowledge is privately, individually accessible. It’s easy to, on your own without anyone knowing, get a laptop and start learning to program, learning to program AI, and learning to experiment with AI. If you’re super talented, people might pay you to do this! I would guess that this is a lot less true with nuclear and bio stuff?
There’s lots of easily externally checkable benchmarks and test applications to notice progress.