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Explore recent advancements in learning quantum phenomena through this 56-minute conference talk by Jerry Zheng Li at BIMSA. Delve into the fundamental question of extracting information about quantum objects from experiments, a crucial aspect of statistical inference with significant implications for quantum computation verification. Survey the latest findings in quantum learning, with a focus on techniques applicable to near-term quantum devices. Discover how these concepts led to a groundbreaking demonstration of large-scale, information-theoretic quantum advantage on an actual quantum computer, potentially marking a first-of-its-kind achievement. No prior knowledge of quantum computation or information theory is required, making this talk accessible to a wide audience interested in the cutting-edge developments at the intersection of quantum physics and machine learning.
