I’m not sure I understand your questions, can you elaborate/explain them more?
Note that the numbers in this chart don’t represent “There is at least one task of length X that AI can do” but rather “There exist AGIs which can do pretty much all relevant intellectual tasks of length X or less.” So my claim is, by the time we get to 2000 in that, such AGIs will be automating huge portions of AI R&D, which will speed it up, which will get us to 10,000 in less than a year, which will speed things up even more, etc.
Yeah, re-reading I realise I was unclear. Given your claim: “by the time we get to 2000 in that, such AGIs will be automating huge portions of AI R&D,”. I’m asking the following:
Is the 2000 mark predicated on automation of things we can’t envision now (finding secret sauce to singularity) or is it predicated off pushing existing things like AI R&D finds better compute or is it a combination of both?
What’s the empirical on the ground representative modal action you’re seeing at 2025 from either your vignette (e.g. I found the diplomacy AI super important for grokking what short timelines were to me). I guess it’s more asking what you see as the divergence between you and Richard at 2025 that’s represented by the difference of 25 and 100.
A bit of both I guess? Insofar as there are things we can’t imagine now, but that a smart hardworking human expert could do in 2000 seconds if and when the situation arose / if and when they put their mind to it, then those things will be doable by AI in 2026 in my median projection.
Unfortunately, my view and Richard’s views don’t really diverge strongly until it’s pretty much too late, as you can see from the chart. :( I think both of us will be very interested in trying to track/measure growth in t-AGI, but he’d be trying to measure the growth rate and then assume it continues going at that rate for years and years, whereas I’d be trying to measure the growth rate so I can guess at how long we have left before it ‘goes critical’ so to speak. For ‘going critical’ we can look at how fast AI R&D is going and try to measure and track that and notice when it starts to speed up due to automation. It’s already probably sped up a little bit, e.g. Copilot helping with coding...
Oooh, thanks for pointing out the typo! Fixed.
I’m not sure I understand your questions, can you elaborate/explain them more?
Note that the numbers in this chart don’t represent “There is at least one task of length X that AI can do” but rather “There exist AGIs which can do pretty much all relevant intellectual tasks of length X or less.” So my claim is, by the time we get to 2000 in that, such AGIs will be automating huge portions of AI R&D, which will speed it up, which will get us to 10,000 in less than a year, which will speed things up even more, etc.
Yeah, re-reading I realise I was unclear. Given your claim: “by the time we get to 2000 in that, such AGIs will be automating huge portions of AI R&D,”. I’m asking the following:
Is the 2000 mark predicated on automation of things we can’t envision now (finding secret sauce to singularity) or is it predicated off pushing existing things like AI R&D finds better compute or is it a combination of both?
What’s the empirical on the ground representative modal action you’re seeing at 2025 from either your vignette (e.g. I found the diplomacy AI super important for grokking what short timelines were to me). I guess it’s more asking what you see as the divergence between you and Richard at 2025 that’s represented by the difference of 25 and 100.
Hopefully that made the questions clearer.
A bit of both I guess? Insofar as there are things we can’t imagine now, but that a smart hardworking human expert could do in 2000 seconds if and when the situation arose / if and when they put their mind to it, then those things will be doable by AI in 2026 in my median projection.
Unfortunately, my view and Richard’s views don’t really diverge strongly until it’s pretty much too late, as you can see from the chart. :( I think both of us will be very interested in trying to track/measure growth in t-AGI, but he’d be trying to measure the growth rate and then assume it continues going at that rate for years and years, whereas I’d be trying to measure the growth rate so I can guess at how long we have left before it ‘goes critical’ so to speak. For ‘going critical’ we can look at how fast AI R&D is going and try to measure and track that and notice when it starts to speed up due to automation. It’s already probably sped up a little bit, e.g. Copilot helping with coding...