Forecasting earthquakes is an important problem in Earth science, because of their devastating consequences. The success of earthquake prediction can potentially save many lives. Current scientific studies related to earthquake prediction focus on when and where it will occur and its magnitude. Different technologies have been used to address this, such as mathematical analysis, machine learning algorithms like […]

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A Quantum counting algorithm is for efficiently counting the number of solutions for a given search problem. The algorithm is based on the quantum phase estimation algorithm and on Grover’s search algorithm. Counting problems are common in diverse fields such as statistical estimation, statistical physics, networking, etc. As for quantum computing, the ability to perform quantum counting efficiently is needed in order to use […]

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The feasibility of a commercial quantum computer was discussed in a prior blog. It was also mentioned that an internet quantum computer service is feasible. While companies like D-Wave in Canada is a commercial quantum computer company, their customers typically ask for build-to-order machines.  Several companies, such as Microsoft, Intel, and IBM have internet-based quantum […]

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Purdue University engineers have addressed an issue barring the development of quantum networks that are big enough to reliably support more than a handful of  users. The method, demonstrated in a paper published in Optica, could help lay the groundwork for when a large number of quantum computers, quantum sensors and other quantum  technology are ready to go […]

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Artificial intelligence (AI) is evolving rapidly, with new neural network models, techniques, and use cases emerging regularly.  While there is no single architecture that works best for all machine and deep learning applications, FPGAs can offer distinct advantages over GPUs and other types of hardware in certain use cases. FPGA DEEP LEARNING BENEFITS:  • FPGAs offer incredible flexibility and cost efficiency […]

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