MIT boffin: Big data won’t compute? Try these handy quantum algorithms

Big Data? Check! Machine Learning? Check! Quantum computers? Check! Seth Lloyd, the self-dubbed “Quantum Mechanic”, has ticked every box with a new (entirely theoretical) paper announcing a potential solution to problems unfeasible even before “the most powerful modern supercomputers”. The paper, titled “Quantum algorithms for topological and geometric analysis of data” was published in Nature Communications on Monday, proposes a theory as to how quantum computers may be used to solve the difficulties in big data analytics. Written by Lloyd, who works at MIT, along with Silvano Garnerone of the University of Waterloo and Paolo Zanardi of the University of Southern California, the paper explains how algebraic topology could help to “reduce the impact of the inevitable distortions that arise every time someone collects data about the real world.” Topology…


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