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

January 25, 2016
Aaron Polmeer

By Katherine Noyes

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 algorithm can streamline highly complex problems and put solutions within closer reach.

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