AI 中文总结
探讨人工智能与量子计算进展，指出经典机器学习助量子计算，量子机器学习利用两种范式优势，认为二者相互受益，回顾量子计算中机器学习机会，望促成两领域互利的良性循环。
AI 中文摘要
近年来，人工智能和量子计算都取得了巨大进展，为加速科学发现开辟了新途径。经典机器学习已被证明对解决量子计算中的挑战有用，硬件也在朝着早期容错状态发展。另一方面，量子机器学习领域旨在通过开发受益于在量子设备上运行或在量子数据上训练的学习算法或模型，利用两种计算范式的优势。我们认为这两种范式将相互受益。本文回顾了量子计算中机器学习最显著的机会，希望激发一个良性循环，使两个领域相互受益。
英文摘要
Artificial intelligence and quantum computing have both seen tremendous progress in recent years, opening up new avenues for accelerating scientific discovery. Classical machine learning has already proven to be useful for addressing challenges in quantum computation; and hardware progress is well underway towards the early fault-tolerant regime. On the other hand, the emerging field of quantum machine learning is aimed at utilizing the strengths of both computational paradigms, via the development of learning algorithms or models that benefit from running on quantum devices or from training on quantum data. We therefore argue that both of these paradigms stand to benefit substantially from each other. Here we review the most salient opportunities for machine learning in quantum computing, hoping to inspire a virtuous cycle through which both fields can mutually benefit.
