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.
At CES 2019 today, IBM announced its first commercial quantum computing system. The system, which doesn't have a price, measures in at a whopping 9' cube.
As molecules go, beryllium hydride is puny—just two hydrogen atoms tacked onto a single beryllium atom. But, for the moment, it’s a heavyweight champ: It’s now the largest molecule ever modeled on a quantum computer, an emerging technology that might someday solve problems that stymie ordinary computers. The advance, though still in the realm of what ordinary computers can do, could provide a stepping stone toward a powerful new way to discover new drugs and materials.
Researchers in China, led by expert Pan Jianwei, may have created the quantum computer destined to outperform all supercomputers.
