Institute of Physics, University of Münster, Münster, Germany.
Organic Chemistry Institute, University of Münster, Münster, Germany.
Nature. 2021 Jun;594(7863):345-355. doi: 10.1038/s41586-021-03453-y. Epub 2021 Jun 16.
Artificial intelligence (AI) is accelerating the development of unconventional computing paradigms inspired by the abilities and energy efficiency of the brain. The human brain excels especially in computationally intensive cognitive tasks, such as pattern recognition and classification. A long-term goal is de-centralized neuromorphic computing, relying on a network of distributed cores to mimic the massive parallelism of the brain, thus rigorously following a nature-inspired approach for information processing. Through the gradual transformation of interconnected computing blocks into continuous computing tissue, the development of advanced forms of matter exhibiting basic features of intelligence can be envisioned, able to learn and process information in a delocalized manner. Such intelligent matter would interact with the environment by receiving and responding to external stimuli, while internally adapting its structure to enable the distribution and storage (as memory) of information. We review progress towards implementations of intelligent matter using molecular systems, soft materials or solid-state materials, with respect to applications in soft robotics, the development of adaptive artificial skins and distributed neuromorphic computing.
人工智能(AI)正在加速发展非传统的计算范式,这些范式受到大脑的能力和能效的启发。人脑在计算密集型认知任务方面表现出色,例如模式识别和分类。一个长期目标是去中心化的神经形态计算,依赖于一个分布式核心网络来模拟大脑的大规模并行性,从而严格遵循受自然启发的信息处理方法。通过将互联的计算块逐渐转变为连续的计算组织,可以设想开发出具有基本智能特征的先进物质形式,这些物质能够以非局部的方式学习和处理信息。这种智能物质将通过接收和响应外部刺激与环境进行交互,同时内部调整其结构以实现信息的分布和存储(作为记忆)。我们综述了使用分子系统、软物质或固态材料实现智能物质的进展,以及在软机器人、自适应人工皮肤和分布式神经形态计算方面的应用。