Agree with what you’re saying. This part of the review in particular stood out to me:
In pure Bayesian reasoning, if one has several uncertain measurements of the same value, each represented by a probability distribution...
Since Cotra isn’t presenting the different anchors as all-things-considered estimates, but instead more like different hypotheses. Consider the evolutionary anchor – Cotra could have divided the compute requirements in this anchor by a scaling factor for how much more efficient she believes human-directed SGD (or similar) will be compared to how efficient evolution was at finding intelligence, yielding an all-things-considered estimate of how much compute will be necessary for TAI, but instead she leaves the value as is and considers it a soft upper bound.
Agree with what you’re saying. This part of the review in particular stood out to me:
Since Cotra isn’t presenting the different anchors as all-things-considered estimates, but instead more like different hypotheses. Consider the evolutionary anchor – Cotra could have divided the compute requirements in this anchor by a scaling factor for how much more efficient she believes human-directed SGD (or similar) will be compared to how efficient evolution was at finding intelligence, yielding an all-things-considered estimate of how much compute will be necessary for TAI, but instead she leaves the value as is and considers it a soft upper bound.