When Brain-inspired AI Meets AGI
- URL: http://arxiv.org/abs/2303.15935v1
- Date: Tue, 28 Mar 2023 12:46:38 GMT
- Title: When Brain-inspired AI Meets AGI
- Authors: Lin Zhao, Lu Zhang, Zihao Wu, Yuzhong Chen, Haixing Dai, Xiaowei Yu,
Zhengliang Liu, Tuo Zhang, Xintao Hu, Xi Jiang, Xiang Li, Dajiang Zhu,
Dinggang Shen, Tianming Liu
- Abstract summary: We provide a comprehensive overview of brain-inspired AI from the perspective of Artificial General Intelligence.
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.
- Score: 40.96159978312796
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
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