TY - JOUR
T1 - When brain-inspired AI meets AGI
AU - Zhao, Lin
AU - Zhang, Lu
AU - Wu, Zihao
AU - Chen, Yuzhong
AU - Dai, Haixing
AU - Yu, Xiaowei
AU - Liu, Zhengliang
AU - Zhang, Tuo
AU - Hu, Xintao
AU - Jiang, Xi
AU - Li, Xiang
AU - Zhu, Dajiang
AU - Shen, Dinggang
AU - Liu, Tianming
N1 - Publisher Copyright:
© 2023 The Authors
PY - 2023/6
Y1 - 2023/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85203186426&partnerID=8YFLogxK
U2 - 10.1016/j.metrad.2023.100005
DO - 10.1016/j.metrad.2023.100005
M3 - 文献综述
AN - SCOPUS:85203186426
SN - 2950-1628
VL - 1
JO - Meta-Radiology
JF - Meta-Radiology
IS - 1
M1 - 100005
ER -