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用于人工智能的脑类器官计算

Brain Organoid Computing for Artificial Intelligence.

作者信息

Cai Hongwei, Ao Zheng, Tian Chunhui, Wu Zhuhao, Liu Hongcheng, Tchieu Jason, Gu Mingxia, Mackie Ken, Guo Feng

出版信息

bioRxiv. 2023 Mar 1:2023.02.28.530502. doi: 10.1101/2023.02.28.530502.

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 , living AI hardware that harnesses the computation power of 3D biological neural networks in a brain organoid. Brain-like 3D 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.

摘要

受大脑启发的硬件模仿生物大脑的结构和工作原理,可能解决快速发展的人工智能(AI)的硬件瓶颈问题。当前受大脑启发的硅芯片前景广阔,但在将其能力充分用于模仿大脑功能以进行人工智能计算方面仍存在限制。在此,我们开发了一种活体人工智能硬件,该硬件利用脑类器官中三维生物神经网络的计算能力。类似大脑的三维培养物通过多电极阵列接收和发送信息来进行计算。应用时空电刺激,这种方法不仅展现出非线性动力学和衰退记忆特性,还能从训练数据中学习。进一步的实验证明了其在求解非线性方程方面的实际应用。这种方法可能为人工智能硬件提供新的见解。

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