Explore the intersection of chemical reaction networks and machine learning in this comprehensive lecture. Delve into the concept of detailed balanced chemical reaction networks and their relationship to generalized Boltzmann machines. Examine key topics including machine learning fundamentals, Boltzmann machines, biology motivations, and the Product Poisson Theorem. Investigate complex distributions, hidden units, energy clamping, and in silico examples. Learn about autonomous learning techniques, thermodynamics applications, and the implications of breaking detailed balance. Gain insights into this interdisciplinary field through a structured presentation followed by a Q&A session.