Subtleties can be hard to convey in text. "Novel scope" just meant the scope beyond training data, discoverable by experimenting, that a post-trained model was

Subtleties can be hard to convey in text. "Novel scope" just meant the scope beyond training data, discoverable by experimenting, that a post-trained model was able to generalize well to. It didn't mean arbitrary or alien to training data. Thesis: The greater a model's scope of generalization, the greater evidence for "understanding" instead of fitting. I can't think of a better way to compare levels of understanding, for models of comparable size, than by how far each of them can generalize beyond training data. I didn't always follow you either. But I didn't think you were being flippant or unreasonable when I didn't. No worries. I appreciated being pushed to think more clearly, and you made points that improved my thinking directly. EDIT ——— I think trading walls of text was a challenge. It seemed sensible to try and respond to "everything", but I can see that one specific at a time would have worked better. And I need to find someone in my vicinity to bash ideas with. I have settled in a new area, and miss that. So thanks.