The Holy Grail of Quantum Artificial Intelligence: Challenges in Accelerating the Machine Learning Pipeline

Abstract

We discuss the synergetic connection between quantum computing and artificial intelligence. After surveying current approaches to quantum artificial intelligence and relating them to a formal model for machine learning processes, we deduce four major challenges for the future of quantum artificial intelligence: (i) Replace iterative training with faster quantum algorithms, (ii) distill the experience of larger amounts of data into the training process, (iii) allow quantum and classical components to be easily combined and exchanged, and (iv) build tools to thoroughly analyze if observed benefits really stem from quantum properties of the algorithm.

Publication
1st International Workshop on Quantum Software Engineering (Q-SE 2020)