This survey examines the interaction between artificial intelligence and quantum information in both directions. It covers AI applications for extracting information from limited quantum measurements, discovering and training quantum algorithms, stabilizing noisy hardware, automating experiments and programming, and extending learning methods to quantum sensing and networking. It also reviews how quantum computation and quantum-inspired structures may affect AI through algorithmic speedups, expressivity, trainability, generalization, neural-network design, and tensor networks. The paper concludes with challenges involving reproducibility, scalability, hardware realism, and quantum-classical co-design.
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