Seán Ó hÉigeartaigh from the University of Cambridge argues compute requirements will constrain AI takeoff speeds since current systems have not automated their own research.

We are in a "slow takeoff" world as per Christiano's definition, and people continue to point to "AI is impressive and has increasingly large effects on the world already" as evidence against it. Fool that IS what is called "slow". "Fast" means "you wake up and Altman is king".

people don't like to read https://sideways-view.com/2018/02/24/takeoff-speeds/

This is true. But right now AI system efficiency, while improving, is not improving as fast as other things. Self-improving AI will no doubt find ways to increase that improvement. But it seems reasonable to expect that compute will remain a constraint at least for a while. (especially if AI needs compute to run lots of experiments in parallel as part of that improvement process).

@S_OhEigeartaigh @neocentrist Only if the compute needs hold constant! Current AIs are trained on like 500 million watts. A human brain runs on like 20. Data efficiency is a similar story. AIs figuring out how to make radically more efficient minds is one route to a foom.

@S_OhEigeartaigh @neocentrist I agree. I think this is a sensible reason why it might take a little while before a foom starts. (I still think it's pretty crazy to imagine that a foom doesn't happen *eventually* -- eventually AIs start figuring out intelligence well enough to design it, etc.)