瓶颈
计算机科学
类有机物
人工神经网络
计算
人工智能
计算机硬件
计算机体系结构
神经科学
嵌入式系统
算法
生物
作者
Hongwei Cai,Zheng Ao,Chunhui Tian,Zhuhao Wu,Hongcheng Liu,Jason Tchieu,Mingxia Gu,Ken Mackie,Feng Guo
标识
DOI:10.1101/2023.02.28.530502
摘要
Abstract Brain-inspired hardware emulates the structure and working principles of a biological brain and may address the hardware bottleneck for fast-growing artificial intelligence (AI). Current brain-inspired silicon chips are promising but still limit their power to fully mimic brain function for AI computing. Here, we develop Brainoware , living AI hardware that harnesses the computation power of 3D biological neural networks in a brain organoid. Brain-like 3D in vitro cultures compute by receiving and sending information via a multielectrode array. Applying spatiotemporal electrical stimulation, this approach not only exhibits nonlinear dynamics and fading memory properties but also learns from training data. Further experiments demonstrate real-world applications in solving non-linear equations. This approach may provide new insights into AI hardware.
科研通智能强力驱动
Strongly Powered by AbleSci AI