AI is expected to transform all industries and that includes Quantum Computing. But unlike other fields Quantum Computing is also transforming AI. In this session we will explore three aspects of this intersection from a Software/Algorithm perspective: a) AI for Quantum, b) Quantum for AI, and finally c) Quantum AI. AI is already impacting Quantum Computing through helping to create new quantum algorithms, optimize quantum circuits and error correction, accelerate benchmarking, optimize control pulses and circuitry, process quantum sensor output, and numerous other enabling capabilities. However, the contrary is also present where quantum inspired algorithms, including those derived from tensor networks, are also inspiring new and improved algorithms for AI. Ultimately as quantum hardware improves this latter may lead to quantum trained AI algorithms. Indeed, there is suggestive evidence that Quantum Machine Learning may significantly reduce the amount of data needed to train AI. This session will explore all three aspects of this interesting intersection.

Moderator

Carl J. Williams CEO CJW Quantum Consulting LLC (United States)

Panelists

Dr. Roman Orus CSO Multiverse Computing (Spain)

Mr. Stefan Cap JD Head of Business Development, North America Riverlane (United States)

Dr. Jeannette “Jamie” Garcia Technical Program Director, Algorithms & Partnerships IBM Quantum (United States)