In the notebook, the number of FLOP to train TAI is deduced a priori. I basically just estimated distributions over the relevant parameters by asking what I’d expect from TAI, rather than taking into consideration whether those values would imply a final distribution that predicts TAI arrived in the past. It may be worth noting that that Bio Anchors also does this initially, but it performs an update by chopping off some probability from the distribution and then renormalizing. I didn’t do that yet because I don’t know how to best perform the update.
Personally, I don’t think a 12% chance that TAI already arrived is that bad, given that the model is deduced a priori. Others could reasonably disagree though.
In the notebook, the number of FLOP to train TAI is deduced a priori. I basically just estimated distributions over the relevant parameters by asking what I’d expect from TAI, rather than taking into consideration whether those values would imply a final distribution that predicts TAI arrived in the past. It may be worth noting that that Bio Anchors also does this initially, but it performs an update by chopping off some probability from the distribution and then renormalizing. I didn’t do that yet because I don’t know how to best perform the update.
Personally, I don’t think a 12% chance that TAI already arrived is that bad, given that the model is deduced a priori. Others could reasonably disagree though.