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Quantum computers are super awesome at matrix multiplication, with some limitations. Quantum superposition allows each bit to be in a lot more states than just zero or one, and quantum gates can fiddle those bits in many different ways. Because of that, a quantum computer can process a lot of information at once for certain applications. One of those ...


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Until we can make a quantum computer with a lot more qubits, the potential to further develop AI will remain just that. D-Wave (which has just made a 2,000+ qubit system around 2015) is an adiabatic quantum computer, not a general-purpose quantum computer. It is restricted to certain optimization problems (at which its effectiveness has reportedly been ...


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Handwritten digit recognition is a standard benchmark in Machine Learning in the form of the MNIST dataset. For example, scikit-learn, a python package for Machine Learning uses it as a tutorial example. The paper you cite uses this standard task as a proof of concept, to show that their system works.


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Quantum computers can help further develop A.I. algorithms and solve the problems to the extent of our creativity and ability to define the problem. For example breaking cryptography can take seconds, where it can takes thousands of years for standard computers. The same with artificial intelligence, it can predict all the combinations for the given problem ...


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It depends a bit on what you mean by 'quantum computer'. The 'conventional' notion is that quantum computation buys a (in some cases, exponential) speedup - it doesn't change what can be computed, just how quickly. In contrast, advocates of hypercomputation claim that quantum effects may make it possible to do infinite computations in finite time. Note, ...


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I think you are looking for quantum machine learning (QML), which is a relatively new field that sits at the intersection of quantum computing and machine learning. If you are not familiar with quantum computing (QC) and you are interested in QML, I suggest that you follow this course by prof. Umesh Vazirani and read the book Quantum Computing for Computer ...


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There are at least these reasons behind (without going too much in detail what is new knowledge and which not in this particular case): Science in level of papers and publications does not always (nor any time?) go with giant leaps. There are hundreds or thousands of people researching one big topic and when everyone takes their own little steps, the entire ...


2

No, quantum computers (as understood by mainstream scientists) cannot solve the halting problem. We can already simulate quantum circuits with normal computers; it just takes a really long time when you get a decent number of qubits involved. (Quantum computing provides exponential speedups for some problems.) Therefore, if quantum computers could solve the ...


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Preface "Before answering this question, let me preface by stating that the following is simply MY answer as a Machine Learning Researcher and "Hobbyist" Theoretical Physicist, although I have strong feelings that my answer will most certainly be proven as true, I am more than sure that others will have differing opinions as with everything else ...


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Well, this is quite deep question. I would recommend you to have a look on the UK physicist Roger Penrose: https://en.wikipedia.org/wiki/Roger_Penrose He has some books on the theme of consciousness and quantum mechanics. There are however critics of his ideas. One of them is that the quantum effects are too small to direct any considerable influence on the ...


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Digital and Analog The question about analog computing is important. Digital circuitry gained popularity as a replacement for analog circuitry during the four decades between 1975 to 2015 due to three compelling qualities. Greater noise immunity Greater drift immunity (accuracy) No leakage of stored values This quickly led to digital signaling standards, ...


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Short version: Most likely we need them because as our need for faster calculations in less time and higher security rises with the increasing usage of internet, technology and A.I., we need faster and more powerful ways of computing. Quantum computers are in theory much faster and more powerful then conventional computers and also almost "impossible" to ...


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During the first decade of this century (and before that) buying a new computer after 2-3 years used to come with much better features and performance, in terms of processor, than it is now. We all know i7 and i5 are not that much different when it comes to performance for a standard home desktop. As we all know that more the most of the modern technological ...


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Welcome to the AI stack Jake. This probably isn't going to be possible. Modern Psudo-random number generators, like Mersenne Twister, are designed not to have any patterns in them, so there's nothing to learn from. You could however, try something like predicting the values of a broken random number generator, like RANDU. These aren't used anymore, ...


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Direct Answer to Your Question:-- The field where quantum computing and A.I. intersect is called quantum machine learning. A.I. is a developing field, with some background (ala McCarthy of LISP fame). Quantum computing is a virgin field that is largely unexplored. A particular type of complexity interacts with another type of complexity to create a very ...


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