Optoelectronic Neural Networks: A Dawn for Post-Moore's Law Computing?

This review summarizes the rapid development of optoelectronic neural networks in recent years, from the pioneering work in deep learning to the latest advances in building large-scale neural networks using photonic devices. Researchers have explored various optical computing methods, including coherent nanophotonic circuits, diffractive deep neural networks, and photoelectric multiplication to implement deep learning. These studies have not only achieved breakthroughs in image recognition and StarCraft, but also provide new possibilities for breaking the limitations of Moore's Law and exploring new paths for post-Moore's Law computing.