| Literature DB >> 28905917 |
Jacob Biamonte1,2, Peter Wittek3, Nicola Pancotti4, Patrick Rebentrost5, Nathan Wiebe6, Seth Lloyd7.
Abstract
Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.Year: 2017 PMID: 28905917 DOI: 10.1038/nature23474
Source DB: PubMed Journal: Nature ISSN: 0028-0836 Impact factor: 49.962