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Quantum Machine Learning is the use of Quantum Computers to do Machine Learning. The Machine Learning techniques applied often are “classical” or do not significantly differ from standard Machine Learning, although the algorithms may be implemented to be optimized for quantum computing.
Sabre Kais, professor of chemical physics at Purdue, said that “this is an exciting time to combine machine learning with quantum computing. Impressive progress has been made recently in building quantum computers, and quantum machine learning techniques will become powerful tools for finding new patterns in big data.”
Jörg Esser, theoretical physicist, wrote that “Quantum computing enables exponential increases in speed by harnessing the weirdness of quantum mechanics. The key challenge is to build robust systems at scale.”
The MIT tech review said that “Quantum computers will be particularly suited to factoring large numbers…, solving complex optimization problems, and executing machine-learning algorithms. And there will be applications nobody has yet envisioned.”