Prospects and Challenges for Quantum Machine Learning - Class 2

Explore the cutting-edge field of quantum machine learning in this comprehensive lecture by Marco Cerezo from Los Alamos National Laboratory. Delve into the promising prospects and complex challenges facing this emerging discipline, gaining insights into how quantum computing could revolutionize machine learning algorithms and applications. Examine the potential advantages of quantum systems in processing and analyzing large datasets, as well as the technical hurdles that must be overcome to realize these benefits. Learn about current research directions, experimental implementations, and theoretical frameworks shaping the future of quantum machine learning. Suitable for advanced students and researchers in quantum computing, machine learning, and related fields, this 1-hour 26-minute talk provides a deep dive into the state-of-the-art at the intersection of quantum physics and artificial intelligence.

Marco Cerezo: Prospects and Challenges for Quantum Machine Learning - Class 2