http://dwave.wordpress.com/2011/10/31/historic-opening-of-the-worlds-first-quantum-computing-centre/

They have already solved some problems on the 128 qubit processor which do not appear solvable using current compute hardware.

The problem I'm most interested in is the solution of binary classifier problem. (Eg is there a picture of grandma in this photo or not, or should the car make a left turn or not). To make these decision you put together a bunch of small simple questions, is that pixel blue, is the pixel next to it grey, etc together with a set of weights and then run a simple calculation which says yes/no. The hard part is calculating the weights when you have a large number of simple classifiers. This is what is classified as NP hard problem, for large numbers of weights the problem cannot be solved on a normal computer.

The dwave computer appears to solve this in polynomial time.

But the kicker is that the output (the weights) can then be used by even simple (smaller than an iphone) computer to perform the classification better more accurately than ever before.

Imagine a future not far from now when every android device is trained specifically to recognize all your specific friends photos, or understand your specific speech patterns, and maybe do it better than even you friends or family do.

The device just needs a set of patterns which are calculated by a dwave processor and then stored for use on all your Google connected devices.

This is why Google is interested in this. Quantum computing doesnt just let use solve hard problems in protean folding, or cryptography, but it lets us turn existing hardware into 'smart' hardware by pushing a small set of bits at the hardware that take enormous amount of compute resources to calculate.

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