> In ML not everything can be derived from theory. And not every theory in ML has a lot of applications to practice. For example, statistical learning theory h

> In ML not everything can be derived from theory. And not every theory in ML has a lot of applications to practice. For example, statistical learning theory has only limited relevance in practice, and algorithmic learning theory has basically none at all. There are a lot of mathematical theories that are relatively old (often much older than the deep learning boom and definitely older than transformers) and that are more interesting from a conceptual perspective rather than from the point of practical applications.