Quantum Computing Technique Harnesses Noise

Researchers at the University of Washington (UW) have developed optical computing hardware for AI and machine learning that is faster and more energy efficient than conventional electronics-based computers. The work also addresses another challenge: the “noise” that is inherent to optical computing and that can interfere with computational precision. The team demonstrated that its system can mitigate noise and that it can use some of it as an input to help enhance the creative output of the artificial neural network within the system. “We’ve built an optical computer that is faster than a conventional digital computer,” said lead author Changming Wu, a UW doctoral student in electrical and computer...