In spite of I had the university course on quantum computing, I am not able to make head or tails of it. (See my recent post about our university education) But, as far as I know, the key idea is a computer can perform exhaustive search in constant time. This means that for quantum algorithms P=NP. For example, the problem of exact MAP inference in an MRF could be efficiently solved via exhaustive search in the space of all possible assignments.
However, quantum computers return probabilistic results, so there remains a work for mathematicians. But it is the work of the different kind. In the field of MRF MAP inference, all the algorithms like loopy BP will be forgotten. Another example: Google's Hartmut Neven developed a quantum version of AdaBoost. So, machine learners, go study quantum mechanics!
rock on! Actually i've thought about machine learning with quantum computing and algorithms before the news (2009?), but it's nice its going the right way, and hopefully someday i'll be contributing to it too!
ReplyDeleteExcellent article. Very interesting to read. I really love to read such a nice article. Thanks! keep rocking.Data Science online Course Bangalore
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