Subtitle: Once AIs match top humans, what are the returns to further scaling and algorithmic improvement?.

This is more speculative and confusing than my typical posts and I also think the content of this post could be substantially improved with more effort. But it's been sitting around in my drafts for a long time and I sometimes want to reference the arguments in it, so I thought I would go ahead and post it.

I often speculate about how much progress you get in the first year after AIs fully automate AI R&D within an AI company (if people try to go as fast as possible). Natural ways of estimating this often involve computing algorithmic research speed-up relative to prior years where research was done by humans. This somewhat naturally gets you progress in units of effective compute — that is, as defined by Epoch researchers here, "the [...]

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Outline:

(04:31) The standard deviation model

(12:11) Differences between domains and diminishing returns

(14:19) An alternative approach based on extrapolating from earlier progress

(19:48) Takeaways

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First published:

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Narrated by TYPE III AUDIO.