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For the first time, physicists have performed machine learning on a photonic quantum computer, demonstrating that quantum computers may be able to exponentially speed up the rate at which certain machine learning tasks are performed—in some cases, reducing the time from hundreds of thousands of years to mere seconds. The new method takes advantage of quantum entanglement, in which two or more objects are so strongly related that paradoxical effects often arise since a measurement on one object instantaneously affects the other. Here, quantum entanglement provides a very fast way to classify vectors into one of two categories, a task that is at the core of machine learning.

The physicists, Chao-Yang Lu, Nai-Le Liu, Li Li and colleagues at the University of Science and Technology of China in Hefei, have published a paper on the entanglement-based machine learning method in a recent issue of Physical Review Letters.

From hundreds of thousands of years to a few seconds is quite an improvement. To read more, click here.