Oatmeal Agitante

not sure I understand the distinction you're making, specifically, what is the distinction between model and explanation?

if a model is optimized for making predictions, it may not be useful for e.g. producing counterexamples to other models

by "explanation" I mean a thing that acts on existing models to change/improve them

really though, the only reason I could say that of the former is that it is "under-specified" compared to the latter

so the former *might* be useful for explanations, or maybe not. but the latter seems optimized for something else

(also, everything I'm expressing here is based on my present contending with Popperian epistemology)

what if I specify that the latter learns; that its models continue to make good predictions in new situations?

what you're saying is rather abstract to me, can you give an example (tweet size permitting)