As quantum computing continues to advance, so too are the algorithms used for quantum machine learning, or QML. Over the past few years, practitioners have been using variational noisy intermediate-scale quantum (NISQ) algorithms designed to compensate for noisy computing environments. “There's a lot of machine learning algorithms in that vein that run in that kind of way. You treat your quantum program as if it was a neural network,” says Joe Fitzsimons, founder and CEO Horizon Quantum Computi...
To read the content, please register or login