Well, I agree that if two worlds I had in mind were 1) foom without real AI progress beforehand 2) continuous progress, then seeing more continuous progress from increased investments should indeed update me towards 2).
The key parameter here is substitutability between capital and labor. In what sense is Human Labor the bottleneck, or is Capital the bottleneck. From the different growth trajectories and substitutability equations you can infer different growth trajectories. (For a paper / video on this see the last paragraph here).
The world in which dalle-2 happens and people start using Github Copilot looks to me like a world where human labour is substitutable by AI labour, which right now is essentially being part of Github Copilot open beta, but in the future might look like capital (paying the product or investing in building the technology yourself). My intuition right now is that big companies are more bottlenecked by ML talent than by capital (cf. the “are we in ai overhang” post explaining how much more capital could Google invest in AI).
Yes, I definitely think that there is quite a bit of overhead in how much more capital businesses could be deploying. GPT-3 is ~$10M, whereas I think that businesses could probably do 2-3OOM more spending if they wanted to (and a Manhattan project would be more like 4OOM bigger/$100B ).
Well, I agree that if two worlds I had in mind were 1) foom without real AI progress beforehand 2) continuous progress, then seeing more continuous progress from increased investments should indeed update me towards 2).
The key parameter here is substitutability between capital and labor. In what sense is Human Labor the bottleneck, or is Capital the bottleneck. From the different growth trajectories and substitutability equations you can infer different growth trajectories. (For a paper / video on this see the last paragraph here).
The world in which dalle-2 happens and people start using Github Copilot looks to me like a world where human labour is substitutable by AI labour, which right now is essentially being part of Github Copilot open beta, but in the future might look like capital (paying the product or investing in building the technology yourself). My intuition right now is that big companies are more bottlenecked by ML talent than by capital (cf. the “are we in ai overhang” post explaining how much more capital could Google invest in AI).
Yes, I definitely think that there is quite a bit of overhead in how much more capital businesses could be deploying. GPT-3 is ~$10M, whereas I think that businesses could probably do 2-3OOM more spending if they wanted to (and a Manhattan project would be more like 4OOM bigger/$100B ).