Kutluyarov Ruslan V, Zakoyan Aida G, Voronkov Grigory S, Grakhova Elizaveta P, Butt Muhammad A
School of Photonics Engineering and Research Advances (SPhERA), Ufa University of Science and Technology, 32, Z. Validi St., 450076 Ufa, Russia.
Samara National Research University, 443086 Samara, Russia.
Nanomaterials (Basel). 2023 Dec 14;13(24):3139. doi: 10.3390/nano13243139.
Neuromorphic photonics is a cutting-edge fusion of neuroscience-inspired computing and photonics technology to overcome the constraints of conventional computing architectures. Its significance lies in the potential to transform information processing by mimicking the parallelism and efficiency of the human brain. Using optics and photonics principles, neuromorphic devices can execute intricate computations swiftly and with impressive energy efficiency. This innovation holds promise for advancing artificial intelligence and machine learning while addressing the limitations of traditional silicon-based computing. Neuromorphic photonics could herald a new era of computing that is more potent and draws inspiration from cognitive processes, leading to advancements in robotics, pattern recognition, and advanced data processing. This paper reviews the recent developments in neuromorphic photonic integrated circuits, applications, and current challenges.
神经形态光子学是受神经科学启发的计算与光子技术的前沿融合，旨在克服传统计算架构的限制。其意义在于通过模仿人类大脑的并行性和效率来改变信息处理的潜力。利用光学和光子学原理，神经形态器件能够快速且高效地执行复杂计算。这一创新有望推动人工智能和机器学习发展，同时解决传统硅基计算的局限性。神经形态光子学可能预示着一个更强大且从认知过程中汲取灵感的计算新时代，从而推动机器人技术、模式识别和高级数据处理的进步。本文综述了神经形态光子集成电路、应用及当前挑战的最新进展。
