QC in Machine Learning: Navigating Potential, Understanding Limitations

Title: Quantum Computing in Machine Learning: Navigating Potential, Understanding Limitations
Summary: Quantum computing is at the cutting edge of innovation, presenting unprecedented opportunities in the field of machine learning. However, it's not without its limitations. This webinar will provide a balanced examination of the capabilities and constraints of quantum computers in machine learning tasks. We will delve into the challenges that exist today, including the limitations in solving complex problems and the absence of standardized quantum software. The session will also cover the state-of-the-art in quantum computation, emphasizing error mitigation techniques and the development of quantum programming. Participants will leave with a realistic understanding of how quantum computing is shaping the future of machine learning, what to realistically expect in the near term, and strategies for navigating the current landscape of quantum technology.
Biography: Dr. Leyton-Ortega is a seasoned physicist with a rich background in quantum dissipative systems, evidenced by a robust academic career culminating in a Ph.D. in the field. Dr. Leyton-Ortega's professional journey through the quantum computing industry includes significant roles at Qubitera and Rigetti Computing, leading to their current position with Oak Ridge National Laboratory. As a member of the Quantum Science Center and the Quantum Computational Science Group, Dr. Leyton-Ortega is at the forefront of quantum error mitigation, quantum machine learning, and quantum software development. With hands-on experience in the practicalities of quantum computing, Dr. Leyton-Ortega brings a wealth of knowledge to the ongoing discussion of quantum technologies' potential and challenges.

Moderators: Pawel Gora, CEO of Quantum AI Foundation, Dr. Sebastian Zajac, member of QPoland