CC BY 4.0Niggemann, OliverBeyerer, JürgenKampker, AchimLi, Rui YanFey, GörschwinKritl, AloisDiedrich, AlexanderKühnert, Christian2025-06-162025-06-162025https://doi.org/10.24406/publica-4776https://publica.fraunhofer.de/handle/publica/48864010.24405/2001810.24406/publica-4776Cyber Physical Systems are characterized by their ability to adapt and learn from their environment. Applications include advanced condition monitoring, predictive maintenance, diagnosis tasks, and many other areas. All these applications have in common that Machine Learning and Artificial Intelligence are the key technologies. However, applying ML and AI to CPS poses challenges such as limited data, less understood algorithms, and the need for high algorithm reliability. These topics were a focal point at the 8th ML4CPS-Machine Learning for Cyber-Physical Systems Conference in Berlin, held from March 6th to 7th, where industry and research experts discussed current advancements and new developments.enconference proceeding