Abstract
Photonic neural networks have been developed as a hardware platform to accelerate machine-learning inference. Digital micromirror devices (DMDs) have been playing a critical role in developing a variety of photonic neural networks for their ability to manipulate millions of optical spatial modes in a 2D plane at >10 kHz frame rate. DMDs have not only enabled high-throughput machine-learning inference but also made hardware-in-the-loop training possible with photonic neural networks. In this talk, we will review the functions of DMDs in a plethora of photonic-neural-network architectures and discuss how MEMS-based technologies can enable novel photonic neural networks in future.
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