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Quantum for Machine Learning

Machine Learning (ML) is arguably the most important basic building block of any future Artificial Intelligence (AI). From an isolated stand point ML has many successful examples in use from the voice control of our smart phones to facial recognition and automated marketing, but to truly harness the power of ML, AI needs to integrate data from a large number of ML systems in a way that allows instinctive patterns to drive descisions.

Application Specific Quantum Integrated Circuit [ASQIC]

An Application Specific Quantum Integrated Circuit [ASQIC] is a an active computational resource that uses one or more quantum analog or quantum optical phenomenon to process a specific calculation in parallel way that cannot be achieved by a classical turning machine.

Classical computers solve mathematical problems using an instruction based (step by step) methodology. Whilst modern computers are able to execute many millions of instructions per second, the general problem is that as the difficulty of the problem increases, so do the number of instructions. When the problem is exponential in nature, the time required to solve it rises proportionally and it becomes rapidly obvious that a classical approach will never solve some of the most interesting and complex problems we face as humans.














  



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