This episode of the Physics World Weekly podcast features an interview with the physicist Maria Schuld, who is a senior researcher and software developer at Xanadu – a Toronto-based quantum technology company. She talks about the challenges and rewards of implementing machine-learning systems on quantum computers. Also on hand is the author Kit Chapman, who chats about his latest book Racing Green: How Motorsport Science Can Change the World. He explains how the myriad technologies developed to make racing cars faster and safer have already benefitted society – and how they could help us combat climate change.

Why did you think to combine Qiskit, a quantum-computing framework, with PyTorch, a machine-learning framework? Karel Dumon: Classical machine learning is currently benefiting hugely from the open-source community, and this is something we want to leverage in quantum too. Our project focuses on the potential application of quantum computing for machine learning, but also on the use of machine learning to help progress quantum computing itself. Through our project, we hope to make it easier for machine learning developers to explore the quantum world. Patrick Huembeli: To that effect, it makes Qiskit very accessible for people with a classical machine learning background -- they can treat the quantum nodes just as another layer of their machine learning algorithm.