Today, I was lucky to lecture at Harvard on using deep learning to solve economic models. I took the opportunity to update my slides and add new material on optimization, implicit regularization, and double descent. The slide deck is posted here: sas.upenn.edu/~jesusfv/Slide… The new deck is longer, 156 slides, and I would need around six hours to cover it carefully. So, I welcome any comments or suggestions. I will be teaching the same material next week at Stanford, so any improvement would be fantastic. For instance, today’s students found that my treatment of why expressiveness grows exponentially with depth wasn’t intuitive enough; I need to redesign that part of the deck. I also need to update the semester-long version, which covers much more material. Finally, I am writing a slide deck on reasoning models in economics. Ideas about good sources? I have a preliminary slide deck, but I would rather read more before I post it. Suffice it to say that I find many of the ideas behind reasoning models, such as inference-time compute scaling, quite fascinating. The application of reinforcement learning is also pretty cool, although I am a bit more familiar with that approach. Thanks in advance!