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

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