Artificial General Intelligence (AGI) has been a long-standing goal of humanity, with the aim of creating machines capable of performing any intellectual task that humans can do. To achieve this, AGI researchers draw inspiration from the human brain and seek to replicate its principles in intelligent machines. Brain-inspired artificial intelligence is a field that has emerged from this endeavor, combining insights from neuroscience, psychology, and computer science to develop more efficient and powerful AI systems. In this article, we provide a comprehensive overview of brain-inspired AI from the perspective of AGI. We begin with the current progress in brain-inspired AI and its extensive connection with AGI. We then cover the important characteristics for both human intelligence and AGI (e.g., scaling, multimodality, and reasoning). We discuss important technologies toward achieving AGI in current AI systems, such as in-context learning and prompt tuning. We also investigate the evolution of AGI systems from both algorithmic and infrastructural perspectives. Finally, we explore the limitations and future of AGI.
翻译：通用人工智能（AGI）一直是人类的一个长期目标，旨在创建能够执行人类能够完成的任何智力任务的机器。为了实现这一目标，AGI研究人员从人脑中汲取灵感，力图在智能机器中复制其原理。脑启发型人工智能是从这种努力中崛起的一个领域，它结合了神经科学、心理学和计算机科学的见解，开发出更高效、更强大的AI系统。在本文中，我们从AGI的角度提供了脑启发型AI的全面概述。我们首先介绍了脑启发型AI的当前进展及其与AGI的广泛联系。然后我们涵盖了人类智能和AGI的重要特征（例如，可扩展性、多模式和推理）。我们讨论了实现当前AI系统中的AGI的重要技术，例如上下文学习和提示调优。我们还研究了AGI系统的演变，从算法和基础设施的角度进行了探讨。最后，我们探讨了AGI的局限性和未来。
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