I agree to some extent, though I also wouldn't be surprised if a models ability to evaluate is tied to it's ability to predict. Better predictors evaluate bette

I agree to some extent, though I also wouldn't be surprised if a models ability to evaluate is tied to it's ability to predict. Better predictors evaluate better. I also expect that evaluation ability doesn't grow linearly with prediction ability, so I doubt that a model will be able to fully optimise it's evaluation potential on it's own. Could be wrong though, will be interesting to see. If I'm right on the former and wrong on the latter we could see maybe models self evaluating to an "optimal" state, for whatever it thinks optimal is via self evaluation is anyway. Or this could be a somewhat useful case of overfitting that just refines a few bits.