圣杯
计算机科学
量子
量子计算机
过程(计算)
人工智能
量子机器学习
物理
量子力学
操作系统
万维网
作者
Thomas Gabor,Leo Sünkel,Fabian Ritz,Thomy Phan,Lenz Belzner,Christoph Roch,Sebastian Feld,Claudia Linnhoff‐Popien
标识
DOI:10.1145/3387940.3391469
摘要
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 whether observed benefits really stem from quantum properties of the algorithm.
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