Neural networks are computing models that have been leading progress in Machine Learning (ML) and Artificial Intelligence (AI) applications. In parallel, the first small-scale quantum computing devices have become available in recent years, paving the way for the development of a new paradigm in information processing. Here we give an overview of the most recent proposals aimed at bringing together these ongoing revolutions, and particularly at implementing the key functionalities of artificial neural networks on quantum architectures. We highlight the exciting perspectives in this context, and discuss the potential role of near-term quantum hardware in the quest for quantum machine learning advantage.

神经网络是在机器学习 (ML) 和人工智能 (AI) 应用程序中一直领先的计算模型。与此同时，近年来第一批小型量子计算设备问世，为信息处理新范式的发展铺平了道路。在这里，我们概述了旨在将这些正在进行的革命结合在一起的最新提案，特别是在量子架构上实现人工神经网络的关键功能。我们强调了在这种情况下令人兴奋的观点，并讨论了近期量子硬件在寻求量子机器学习优势方面的潜在作用。