Dwarkesh Patel @dwarkesh_sp
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Dwarkesh Patel @dwarkesh_sp . 13h Full debate from 2021: lesswrong.com/s/n945eovrA3oD... [Christiano][22:57] right now I think hardware R&D is on the order of $100B/year, AI R&D is more like $10B/year, I guess I'm betting on something more like trillions? (limited from going higher because of accounting problems and not that much smart money) I don't think steel production is going up at that point plausibly going down since you are redirecting manufacturing capacity into making more computers. But probably just staying static while all of the new capacity is going into computers, since cannibalizing existing infrastructure is much more expensive the original point was: you aren't pulling AlphaZero shit any more, you are competing with an industry that has invested trillions in cumulative R&D [Yudkowsky][23:00] is this in hopes of future profit, or because current profits are already in the trillions? [Christiano][23:01] largely in hopes of future profit / reinvested AI outputs (that have high market cap), but also revenues are probably in the trillions? [Yudkowsky][23:02] this all sure does sound "pretty darn prohibited" on my model, but I'd hope there'd be something earlier than that we could bet on. what does your Prophecy prohibit happening before that sub-prophesied day? [2 replies, 2 reposts, 71 likes, 11K views] Dwarkesh Patel @dwarkesh_sp . 13h In 2016 (before transformers) Paul wrote, "It's plausible that a large neural network can replicate "fast" human cognition, and that by coupling it to simple computational mechanisms—short and long-term memory, attention, etc.—we could obtain a human-level computational architecture. It's plausible that a variant of RL can train this architecture to actually implement human-level cognition."
Note from Claude Sonnet 5
Continuation of the @dwarkesh_sp thread on Paul Christiano's predictions: a screenshot excerpt of the 2021 LessWrong Christiano/Yudkowsky takeoff-speed debate transcript, followed by the start of a new tweet quoting Christiano's 2016 (pre-transformer) writing on neural networks plausibly reaching human-level cognition.
ai safetytakeoff speedspaul christianoeliezer yudkowskyforecastinglesswrong