Machine Learning using Quantum Algorithms

Could please someone give a layman's explanation for this bombshell?<p>&#62; Assume I hide a ball in a cabinet with a million drawers. How many drawers do you have to open to find the ball? Sometimes you may get lucky and find the ball in the first few drawers but at other times you have to inspect almost all of them. So on average it will take you 500,000 peeks to find the ball. <i>Now a quantum computer can perform such a search looking only into 1000 drawers.</i> This mind boggling feat is known as Grover’s algorithm.<p>If 999,000 drawers are left unopened, how can the algorithm guarantee that the ball will be found?

This is an old article (from 2009). Hartmut Neven provided an update at ICML 2011 in the latter part of his keynote talk - <a href="http://techtalks.tv/talks/54457/" rel="nofollow">http://techtalks.tv/talks/54457/</a>

Non js-heavy version, for those who need/want it:<p><a href="http://googleresearch.blogspot.com/2009/12/machine-learning-with-quantum.html?v=0" rel="nofollow">http://googleresearch.blogspot.com/2009/12/machine-learning-...</a>

Someone should modify the post to note that this is from Dec. 2009. Not sure what to think here. Google is endorsing, but IEEE is slamming. DWave actually has a reasonable looking dev kit on this page, but Scott Aaronson is quite critical.<p><a href="http://spectrum.ieee.org/computing/hardware/loser-dwave-does-not-quantum-compute" rel="nofollow">http://spectrum.ieee.org/computing/hardware/loser-dwave-does...</a><p><a href="http://www.dwavesys.com/en/dev-tutorials.html" rel="nofollow">http://www.dwavesys.com/en/dev-tutorials.html</a><p><a href="http://www.scottaaronson.com/blog/?p=306" rel="nofollow">http://www.scottaaronson.com/blog/?p=306</a><p><a href="http://www.scottaaronson.com/blog/?p=291" rel="nofollow">http://www.scottaaronson.com/blog/?p=291</a><p>Would be nice if a real expert weighed in on this thread.

D-Wave's computer is basically a hardware solver for Ising/QUBO models. It is not programable in the traditional sense and you need to find a way to express the problem you want to solve in a way that maps well over the hardware.

In my line of work I see RAM limitation rather than CPU clock speed limitation. Will this technology also solve the big data problem?

Quantum Algorithms (run on quantum computers) are the future for Machine Learning. This article was from 2009 though, and I haven't seen a whole lot of progress in the field. Artificial Neural Networks that can model every possible value of every node at the same time is very powerful.