[nth_order]

I agree with your views - its great and ultimately enriching that people approach this fascinating field on these varying levels of mathematical rigor. They complement each other nicely. He kind of says it himself, „we are building tools for people to get things done“, meaning there is this utilitarian point to ML, and empirism as a vehicle into the unknown is totally fine. The rigor/theoretical treatment will come over time anyways.

What I can more sympathize with is this notion of „AI colonialism“ happening somewhat. We can‘t trust our ML tools too easily, and should listen to domain experts maybe a bit more than many currently do.

That he criticizes AlphaFold2 is especially interesting I think. That model is clearly very useful, and crucially it is well calibrated and its limitations are in the process of being characterized. The measures of model quality are also not arbitrary at all, they have been used for sometimes decades in the field. If funding dries up - we will see. That would be tragic as there are still many interesting problems to solve there, AF2 should just be a start that enables research in many interesting new directions.