A rigorous intellectual history of machine learning’s mathematical foundations, undermined by its own admission that the theory no longer explains why modern AI works.

A sharp critique of Mollick’s practical AI guide, praising its empirical rigor while questioning whether its optimistic framework can survive the messy realities of adoption.