Explore the integration of machine learning techniques in theorem proving tools in this conference talk from ACM SIGPLAN's CPP'24. Delve into the classification of various learning tasks and examine the tools designed to enhance the efficiency of interactive theorem provers. Learn about successful techniques that improve automation power, focusing on Monte-Carlo simulations guided by reinforcement learning from previous proof attempts. Gain insights into the current and future challenges in the field, including more efficient interaction with interactive theorem provers. Presented by Cezary Kaliszyk, this hour-long talk offers a comprehensive overview of the evolving landscape of machine learning in interactive proof assistance.