When big data gets too big, this machine-learning algorithm may be the answer

Combining topology and quantum computing, it promises to put huge analyses within closer reach Results of an analysis that would be too complex for conventional techniques but can be handled easily by the new quantum approach. Credit: Courtesy of the researchers/MIT IDG News Service Jan 25, 2016 12:56 PM Big data may hold a world of untapped potential, but what happens when your data set is bigger than your processing power can handle? A new algorithm that taps quantum computing may be able to help. That’s according to researchers from MIT, the University of Waterloo and the University of Southern California who published a paper Monday describing a new approach to handling massively complex problems. By combining quantum computing and topology — a branch of geometry — the new machine-learning…


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