神经形态工程学
光子学
计算机科学
多路复用
数码产品
生物光子学
人工智能
领域(数学分析)
人工神经网络
超短脉冲
计算机体系结构
电子工程
深度学习
集成光学
硅光子学
集成电路
信号处理
光学计算
班级(哲学)
信息处理
作者
Bhavin J. Shastri,Alexander N. Tait,T. Ferreira de Lima,Wolfram H. P. Pernice,Harish Bhaskaran,C. D. Wright,Paul R. Prucnal
出处
期刊:Nature Photonics
[Nature Portfolio]
日期:2021-01-29
卷期号:15 (2): 102-114
被引量:1539
标识
DOI:10.1038/s41566-020-00754-y
摘要
Research in photonic computing has flourished due to the proliferation of optoelectronic components on photonic integration platforms. Photonic integrated circuits have enabled ultrafast artificial neural networks, providing a framework for a new class of information processing machines. Algorithms running on such hardware have the potential to address the growing demand for machine learning and artificial intelligence, in areas such as medical diagnosis, telecommunications, and high-performance and scientific computing. In parallel, the development of neuromorphic electronics has highlighted challenges in that domain, in particular, related to processor latency. Neuromorphic photonics offers sub-nanosecond latencies, providing a complementary opportunity to extend the domain of artificial intelligence. Here, we review recent advances in integrated photonic neuromorphic systems, discuss current and future challenges, and outline the advances in science and technology needed to meet those challenges.
科研通智能强力驱动
Strongly Powered by AbleSci AI