Brain-inspired computing uses insights from neuroscience to develop more efficient computing systems. The approach is of use in a broad range of applications—from neural simulation to intelligent computing—and could potentially be used to create a general-purpose computing infrastructure. Here we explore the development of general-purpose brain-inspired computing. We examine the hardware and software that have so far been used to create brain-inspired computing systems. We then consider the potential of combining approaches from neuroscience and computer science to build general-purpose brain-inspired computing systems, highlighting three areas: temporal, spatial and spatiotemporal capabilities; approximate computing and precise computing; and control flow and data flow. Finally, we discuss initiatives that will be needed to develop general-purpose brain-inspired computing, highlighting three potential strategies: application-level pattern generalization, hardware-level structural generalization and software-level systematic generalization.

类脑计算利用神经科学的见解来开发更高效的计算系统。该方法可用于广泛的应用程序（从神经模拟到智能计算），并且可能用于创建通用计算基础设施。在这里，我们探讨了通用类脑计算的发展。我们研究了迄今为止用于创建类脑计算系统的硬件和软件。然后，我们考虑了结合神经科学和计算机科学的方法来构建通用类脑计算系统的潜力，突出了三个领域：时间、空间和时空能力;近似计算和精确计算;以及控制流和数据流。最后，我们讨论了开发通用类脑计算所需的举措，重点介绍了三种潜在策略：应用程序级模式泛化、硬件级结构泛化和软件级系统泛化。