When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...
Quantum computing appears on track to help companies in three main areas: optimization, simulation and machine learning. The appeal of quantum machine learning lies in its potential to tackle problems ...
Pushing against years of scepticism, an analysis suggests quantum computers may offer real advantages for running machine learning and similar algorithms in the near future ...
MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced the proposal of a new approach to solving the Boolean function query problem. This framework starts from the ...
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Quantum’s next step: Making it reliable
During SAS Innovate 2026 in Dallas, principal quantum systems architect Bill Wisotsky tells ARTHUR GOLDSTUCK what will take ...
Also essentially still embryonic, quantum AI is an approach involving running machine learning algorithms on existing quantum hardware to run tasks in hours (instead of weeks) and/or work on rendering ...
Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...
MicroAlgo QAS, by optimizing quantum circuit architectures, can significantly enhance the robustness of VQA in various noisy environments. By automatically searching for suitable circuit designs, QAS ...
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