Challenges in ML Engineering

Explore the evolving landscape of machine learning engineering in this 52-minute talk by Dr. Jukka K. Nurminen from the Finnish Center for Artificial Intelligence FCAI. Delve into the shift from developing smarter models to implementing AI in real-world scenarios. Discover key challenges in MLOps, including cost-efficient inference, automation of ML practices, accuracy monitoring, and anomaly detection. Gain insights from Dr. Nurminen's extensive experience in software research across telecom, academia, and applied research. Learn about the transition towards a more systematic and industrial approach to developing, testing, monitoring, and maintaining ML systems. Understand the importance of addressing these challenges as AI continues to mature and find practical applications in various industries.