I was more making the point that, if we enter a regime where AI can do 10 hour SWE tasks, then this will result in big algorithmic improvements, but at some point pretty quickly effective compute improvements will level out because of physical compute bottlenecks. My claim is that the point at which it will level out will be after multiple years worth of current algorithmic progress had been “squeezed out” of the available compute.
Interesting, thanks for clarifying. It’s not clear to me that this is the right primary frame to think about what would happen, as opposed to just thinking first about how big compute bottlenecks are and then adjusting the research pace for that (and then accounting for diminishing returns to more research).
I think a combination of both perspectives is best, as the argument in your favor for your frame is that there will be some low-hanging fruit from changing your workflow to adapt to the new cognitive labor.
I was more making the point that, if we enter a regime where AI can do 10 hour SWE tasks, then this will result in big algorithmic improvements, but at some point pretty quickly effective compute improvements will level out because of physical compute bottlenecks. My claim is that the point at which it will level out will be after multiple years worth of current algorithmic progress had been “squeezed out” of the available compute.
Interesting, thanks for clarifying. It’s not clear to me that this is the right primary frame to think about what would happen, as opposed to just thinking first about how big compute bottlenecks are and then adjusting the research pace for that (and then accounting for diminishing returns to more research).
I think a combination of both perspectives is best, as the argument in your favor for your frame is that there will be some low-hanging fruit from changing your workflow to adapt to the new cognitive labor.