I recently started a new newsletter focus on AI education and already has over 50,000 subscribers. TheSequence is a no-BS (meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Deep learning is becoming increasingly important across different core scientific disciplines such as biology or physics. Obviously, mathematics is the foundation behind every deep learning method but could these be used to advance math research itself?

One of the exciting directions regarding applications of computers in mathematics is to use them to experimentally form new conjectures. Google's DeepMind launched an endeavor for using machine learning (and deep learning in particular) for finding conjectures based on data. Two recent outcomes are toward the Dyer-Lusztig conjecture (Charles Blundell, Lars Buesing, Alex Davies, Petar Veličković, Geordie Williamson) and for certain new invariants in knot theory (Alex Davies, András Juhász, Marc Lackenby, Nenad Tomasev). There is also a Nature article Advancing mathematics by guiding human intuition with AI, on these developements. Here are also links to a new MO question and an old one on applications of computers to mathematics.