Imagine that you had ChatGPT + AlphaCode + Imagen but without all of the handicaps ChatGPT currently has (won’t discuss sensitive topics, no ability to query/interact with the web). How much worse do you really think that would be than hiring an executive assistant from a service like this?
I myself have 4-year timelines, so this question is best directed at Paul, Ajeya, etc.
However, note that the system you mention may indeed be superior to human workers for some tasks/jobs while not being superior for others. This is what I think is the case today. In particular, most of the tasks involved in AI R&D in 2020 are still being done by humans today; only some single-digit percentage of them (weighted by how many person-hours they take) has been automated. (I’m thinking mainly of Copilot here, which seems to be providing a single-digit percentage speedup on its own basically.)
I guess it’s my median; the mode is a bit shorter. Note also that these are timelines until APS-AI (my preferred definition of AGI, introduced in the Carlsmith report); my timelines until nanobot swarms and other mature technologies is 1-2 years longer. Needless to say I really, really hope I’m wrong about all this. (Wrong in the right way—it would suck to be wrong in the opposite direction and have it all happen even sooner!)
For context, I wrote this story almost two years ago by imagining what I thought was most likely to happen next year, and then the year after that, and so on. I only published the bits up till 2026 because in my draft of 2027 the AIs finally qualify as APS-AI & I found it really difficult to write about & I didn’t want to let perfect be the enemy of the good. Well, in the time since I wrote that story, my timelines have shortened...
So I guess my 10th percentile is 2023, my 25th is 2024, 75th is 2033, and 90th is “hasn’t happened by 2045, either because it’s never gonna happen or because some calamity has set science back or (unlikely, but still possible) AGI turns out to be super duper hard, waaaay harder than I thought.”
If this sounds crazy to you, well, I certainly don’t expect you to take my word for it. But notice that if AGI does happen eventually, you yourself will eventually have a distribution that looks like this. If it’s crazy, it can’t be crazy just in virtue of being short—it has to be crazy in virtue of being so short while the world outside still looks like XYZ. The crux (for craziness) is whether the world we observe today is compatible with AGI happening three years later. (The crux for overall credences would be e.g. whether the world we observe today is more compatible with AGI happening in 3 years, than it is with AGI taking another 15 years to arrive)
Does this have any salient AI milestones that are not just straightforward engineering, on the longer timelines? What kind of AI architecture does it bet on for shorter timelines?
My expectation is similar, and collapsed from 2032-2042 to 2028-2037 (25%/75% quantiles to mature future tech) a couple of weeks ago, because I noticed that the two remaining scientific milestones are essentially done. One is figuring out how to improve LLM performance given lack of orders of magnitude more raw training data, which now seems probably unnecessary with how well ChatGPT works already. And the other is setting up longer-term memory for LLM instances, which now seems unnecessary because day-long context windows for LLMs are within reach. This gives a significant affordance to build complicated bureaucracies and debug them by adding more rules and characters, ensuring that they correctly perform their tasks autonomously. Even if 90% of a conversation is about finagling it back on track, there is enough room in the context window to still get things done.
So it’s looking like the only thing left is some engineering work in setting up bureaucracies that self-tune LLMs into reliable autonomous performance, at which point it’s something at least as capable as day-long APS-AI LLM spurs that might need another 1-3 years to bootstrap to future tech. In contrast to your story, I anticipate much slower visible deployment, so that the world changes much less in the meantime.
I don’t want to get into too much specifics. That said it sounds like we have somewhat similar views, I just am a bit more bullish for some reason.
I wonder if we should make some bets about what visible deployments will look like in, say, 2024? I take it you’ve read my story—wanna leave a comment sketching which parts you disagree with or think will take longer?
Basically, I don’t see chatbots being significantly more useful than today until they are already AGI and can teach themselves things like homological algebra, 1-2 years before the singularity. This is a combination of short timelines not giving time to polish them enough, and polishing them enough being sufficient to reach AGI.
OK. What counts as significantly more useful than today? Would you say e.g. that the stuff depicted in 2024-2026 in my story, generally won’t happen until 2030? Perhaps with a few exceptions?
8x A100′s will run you $8.80/hr on lambdalabs.com.
Imagine that you had ChatGPT + AlphaCode + Imagen but without all of the handicaps ChatGPT currently has (won’t discuss sensitive topics, no ability to query/interact with the web). How much worse do you really think that would be than hiring an executive assistant from a service like this?
I myself have 4-year timelines, so this question is best directed at Paul, Ajeya, etc.
However, note that the system you mention may indeed be superior to human workers for some tasks/jobs while not being superior for others. This is what I think is the case today. In particular, most of the tasks involved in AI R&D in 2020 are still being done by humans today; only some single-digit percentage of them (weighted by how many person-hours they take) has been automated. (I’m thinking mainly of Copilot here, which seems to be providing a single-digit percentage speedup on its own basically.)
Is that a mean, median or mode? Also, what does your probability distribution look like? E.g. what are its 10th, 25th, 75th and/or 90th percentiles?
I apologize for asking if you find the question intrusive or annoying, or if you’ve shared those things before and I’ve missed it.
I guess it’s my median; the mode is a bit shorter. Note also that these are timelines until APS-AI (my preferred definition of AGI, introduced in the Carlsmith report); my timelines until nanobot swarms and other mature technologies is 1-2 years longer. Needless to say I really, really hope I’m wrong about all this. (Wrong in the right way—it would suck to be wrong in the opposite direction and have it all happen even sooner!)
For context, I wrote this story almost two years ago by imagining what I thought was most likely to happen next year, and then the year after that, and so on. I only published the bits up till 2026 because in my draft of 2027 the AIs finally qualify as APS-AI & I found it really difficult to write about & I didn’t want to let perfect be the enemy of the good. Well, in the time since I wrote that story, my timelines have shortened...
So I guess my 10th percentile is 2023, my 25th is 2024, 75th is 2033, and 90th is “hasn’t happened by 2045, either because it’s never gonna happen or because some calamity has set science back or (unlikely, but still possible) AGI turns out to be super duper hard, waaaay harder than I thought.”
If this sounds crazy to you, well, I certainly don’t expect you to take my word for it. But notice that if AGI does happen eventually, you yourself will eventually have a distribution that looks like this. If it’s crazy, it can’t be crazy just in virtue of being short—it has to be crazy in virtue of being so short while the world outside still looks like XYZ. The crux (for craziness) is whether the world we observe today is compatible with AGI happening three years later. (The crux for overall credences would be e.g. whether the world we observe today is more compatible with AGI happening in 3 years, than it is with AGI taking another 15 years to arrive)
Does this have any salient AI milestones that are not just straightforward engineering, on the longer timelines? What kind of AI architecture does it bet on for shorter timelines?
My expectation is similar, and collapsed from 2032-2042 to 2028-2037 (25%/75% quantiles to mature future tech) a couple of weeks ago, because I noticed that the two remaining scientific milestones are essentially done. One is figuring out how to improve LLM performance given lack of orders of magnitude more raw training data, which now seems probably unnecessary with how well ChatGPT works already. And the other is setting up longer-term memory for LLM instances, which now seems unnecessary because day-long context windows for LLMs are within reach. This gives a significant affordance to build complicated bureaucracies and debug them by adding more rules and characters, ensuring that they correctly perform their tasks autonomously. Even if 90% of a conversation is about finagling it back on track, there is enough room in the context window to still get things done.
So it’s looking like the only thing left is some engineering work in setting up bureaucracies that self-tune LLMs into reliable autonomous performance, at which point it’s something at least as capable as day-long APS-AI LLM spurs that might need another 1-3 years to bootstrap to future tech. In contrast to your story, I anticipate much slower visible deployment, so that the world changes much less in the meantime.
I don’t want to get into too much specifics. That said it sounds like we have somewhat similar views, I just am a bit more bullish for some reason.
I wonder if we should make some bets about what visible deployments will look like in, say, 2024? I take it you’ve read my story—wanna leave a comment sketching which parts you disagree with or think will take longer?
Basically, I don’t see chatbots being significantly more useful than today until they are already AGI and can teach themselves things like homological algebra, 1-2 years before the singularity. This is a combination of short timelines not giving time to polish them enough, and polishing them enough being sufficient to reach AGI.
OK. What counts as significantly more useful than today? Would you say e.g. that the stuff depicted in 2024-2026 in my story, generally won’t happen until 2030? Perhaps with a few exceptions?