(InfoQ.com) An important area of research in quantum computing concerns the application of quantum computers to training of quantum neural networks.
Author Sergio De Simone interviews Google Senior research scientist Jarrod McClean to better understand the importance the relationship between quantum computing and machine learning. McClean based his responses on two recent papers published by Google AI Quantum team.
The first post focuses on two fairly distinct results on quantum neural networks. The first shows a general method by which one may use quantum neural networks to attack traditional classification tasks. We feel this may be important as a framework to explore the power of quantum devices applied to traditional machine learning tasks and problems.
The second result is about the existence of a fundamental and interesting phenomenon in the training of quantum neural networks. It reflects the fact that sufficient randomization in a quantum circuit can act almost like a black hole, making it very difficult to get information back out.