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Artificial intelligence (AI) techniques have boosted the capability of optical imaging, sensing, and communication. Concurrently, photonics facilitate the tangible realization of deep neural networks, offering potential benefits in terms of latency, throughput, and energy efficiency. In this talk, I will discuss our efforts in AI photonics with two examples. The first involves employing a convolutional neural network for achieving single-shot full-field measurement of optical signals. The second example pertains to implementing a deep neural network with a multiple-scattering system featuring structural nonlinearity, thereby enabling nonlinear computations using linear optics.
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