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What a compute-centric framework says about AI takeoff speeds — EA Forum

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As part of my work for Open Philanthropy I’ve written a draft report on AI takeoff speeds, the question of how quickly AI capabilities might improve as we approach and surpass human-level AI. Will human-level AI be a bolt from the blue, or will we have AI that is nearly as capable many years earlier? Most of the analysis is from the perspective of a compute-centric framework, inspired by that used in the Bio Anchors report, in which AI capabilities increase continuously with more training compute and work to develop better AI algorithms. This post doesn’t summarise the report. Instead I want to explain some of the high-level takeaways from the research which I think apply even if you don’t buy the compute-centric framework. h/t Dan Kokotajlo for writing most of this section This report accompanies and explains https://takeoffspeeds.com (h/t Epoch for building this!), a user-friendly quantitative model of AGI timelines and takeoff, which you can go play around with right now. (By AGI I

Benjamin Hilton 3y 34 3 1 This looks really cool, thanks Tom! I haven't read the report in full (just the short summary) - but I have some initial scepticism, and I'd love to answers to some of the following questions, so I can figure out how much evidence this report is on takeoff speeds. I've put the questions roughly in order of subjective importance to my ability to update: Did you consider Baumol effects, the possibility of technological deflation, and the possibility of technological unemployment, how they affect the profit incentive as tasks are increasingly automated? [My guess is that

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