The Machine Learning for Physics (ML4Physics) Summer School successfully concluded last week in Ljubljana, Slovenia, bringing together 55 participants — 47 from abroad — for a week-long deep dive into the intersection of machine learning and physics. The school was organized by the COMETA COST Action, SMARTHEP, the SMASH MSCA COFUND, the Jožef Stefan Institute, and the Faculty of Mathematics and Physics at the University of Ljubljana. Its goal was to equip participants from diverse backgrounds with solid knowledge of cutting-edge machine learning topics relevant to physics. Each day combined morning lectures, afternoon hands-on exercises, and evening keynote talks or social and outreach activities. The school featured 11 lecturers and tutors, as well as two keynote talks by Uroš Seljak (UC Berkeley) and Nenad Tomasev (DeepMind), who shared insights from both academia and industry. The ML4Physics Summer School proved to be a vibrant platform for learning, collaboration, and exchange, demonstrating the power of interdisciplinary training in shaping the future of AI in science.