This is not quite true. Raw policy networks of AlphaGo-like models are often at a level around 3 dan in amateur rankings, which would qualify as a good amateur player but nowhere near the equivalent of grandmaster level. If you match percentiles in the rating distributions, 3d in Go is perhaps about as strong as an 1800 elo player in chess, while "master level" is at least 2200 elo and "grandmaster level" starts at 2500 elo.
Edit: Seems like policy networks have improved since I last checked these rankings, and the biggest networks currently available for p...
I think you're ignoring the qualifier "literally portrayed" in Matthew's sentence, and neglecting the prior context that he's talking about AI development being something mainly driven forward by hobbyists with no outsized impacts.
He's talking about more than just the time in which AI goes from e.g. doubling the AI software R&D output of humans to some kind of singularity. The specific details Eliezer has given about this scenario have not been borne out: for example, in his 2010 debate with Robin Hanson, he emphasized a scenario in which a few people ...
Hmm, I do agree the foom debates talk a bunch about a "box in a basement team", but the conversation was pretty explicitly not about the competitive landscape and how many people are working on this box in a basement, etc. It was about whether it would be possible for a box in a basement with the right algorithms to become superhuman in a short period of time. In-particular Eliezer says:
...In other words, I’m trying to separate out the question of “How dumb is this thing (points to head); how much smarter can you build an agent; if that agent were telep
I find myself confused about what point this post is trying to make even after reading through it twice. Can you summarize your central point in 100 words or less?
If the title is meant to be a summary of the post, I think that would be analogous to someone saying "nuclear forces provide an untapped wealth of energy". It's true, but the reason the energy is untapped is because nobody has come up with a good way of tapping into it. A post which tried to address engineering problems around energy production by "we need to look closely at how to extract energy...
If the title is meant to be a summary of the post, I think that would be analogous to someone saying "nuclear forces provide an untapped wealth of energy". It's true, but the reason the energy is untapped is because nobody has come up with a good way of tapping into it.
The difference is people have been trying hard to harness nuclear forces for energy, while people have not been trying hard to research humans for alignment in the same way. Even relative to the size of the alignment field being far smaller, there hasn't been a real effort as far as I can...
I think overall things have been moving faster than I've expected, though only in some dimensions than others. The point about revenue is particularly salient to me and I would now put the complete automation of remotable jobs 30 years out in my median world instead of 40 years out.
Progress on long context coherence, agency, executive function, etc. remains fairly "on trend" despite the acceleration of progress in reasoning and AI systems currently being more useful than I expected, so I don't update down by 2x or 3x (which is more like the speedup we've seen relative to my math or revenue growth expectations).
So your median for the complete automation of remotable jobs is 2055?
... (read more)What about for the existence of AI systems which can completely automate AI software R&D? (So, filling the shoes of the research engineers and research scientists etc. at DeepMind, the members of technical staff at OpenAI, etc.)
What about your 10th percentile, instead of your median?