Li Runze, Yue Zengji, Luan Haitao, Dong Yibo, Chen Xi, Gu Min
School of Artificial Intelligence Science and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China.
Institute of Photonic Chips, University of Shanghai for Science and Technology, Shanghai 200093, China.
Research (Wash D C). 2024 Aug 19;7:0427. doi: 10.34133/research.0427. eCollection 2024.
The rapid development of neuromorphic computing has led to widespread investigation of artificial synapses. These synapses can perform parallel in-memory computing functions while transmitting signals, enabling low-energy and fast artificial intelligence. Robots are the most ideal endpoint for the application of artificial intelligence. In the human nervous system, there are different types of synapses for sensory input, allowing for signal preprocessing at the receiving end. Therefore, the development of anthropomorphic intelligent robots requires not only an artificial intelligence system as the brain but also the combination of multimodal artificial synapses for multisensory sensing, including visual, tactile, olfactory, auditory, and taste. This article reviews the working mechanisms of artificial synapses with different stimulation and response modalities, and presents their use in various neuromorphic tasks. We aim to provide researchers in this frontier field with a comprehensive understanding of multimodal artificial synapses.
神经形态计算的迅速发展引发了对人工突触的广泛研究。这些突触能够在传输信号的同时执行并行内存计算功能,实现低能耗和快速的人工智能。机器人是人工智能应用的最理想终端。在人类神经系统中,存在不同类型的用于感觉输入的突触,可在接收端进行信号预处理。因此,拟人化智能机器人的发展不仅需要一个人工智能系统作为大脑,还需要多模态人工突触的结合以实现多感官感知,包括视觉、触觉、嗅觉、听觉和味觉。本文综述了具有不同刺激和响应模式的人工突触的工作机制,并介绍了它们在各种神经形态任务中的应用。我们旨在为这一前沿领域的研究人员提供对多模态人工突触的全面理解。