Moreover, this is an estimate of effective FLOP, meaning that Cotra takes into account the possibility that software efficiency progress can reduce the physical computational cost of training a TAI system in the future. It was also in units of 2020 FLOP, and we’re already in 2023, so just on that basis alone, these numbers should get adjusted downwards now.
Isn’t it a noted weakness of Cotra’s approach that most of the anchors don’t actually depend on 2020 architecture or algorithmic performance in any concrete way? As in, if the same method were applied today, it would produce the same numbers in “2023 FLOP”? This is related to why I think the Beniaguev paper is pretty relevant exactly as evidence of “inefficiency of our algorithms compared to the human brain”.
Isn’t it a noted weakness of Cotra’s approach that most of the anchors don’t actually depend on 2020 architecture or algorithmic performance in any concrete way? As in, if the same method were applied today, it would produce the same numbers in “2023 FLOP”? This is related to why I think the Beniaguev paper is pretty relevant exactly as evidence of “inefficiency of our algorithms compared to the human brain”.