Summary of Brain-inspired and Self-based Artificial Intelligence, by Yi Zeng et al.
Brain-inspired and Self-based Artificial Intelligence
by Yi Zeng, Feifei Zhao, Yuxuan Zhao, Dongcheng Zhao, Enmeng Lu, Qian Zhang, Yuwei Wang, Hui Feng, Zhuoya Zhao, Jihang Wang, Qingqun Kong, Yinqian Sun, Yang Li, Guobin Shen, Bing Han, Yiting Dong, Wenxuan Pan, Xiang He, Aorigele Bao, Jin Wang
First submitted to arxiv on: 29 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Neurons and Cognition (q-bio.NC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel Brain-inspired and Self-based Artificial Intelligence (BriSe AI) paradigm is introduced in this paper, which aims to build human-level AI models and robotic applications. The BriSe AI emphasizes the crucial role of the Self in shaping the future AI, rooted with a practical hierarchical Self framework that includes Perception and Learning, Bodily Self, Autonomous Self, Social Self, and Conceptual Self. This framework highlights self-based environment perception, self-bodily modeling, autonomous interaction with the environment, social interaction and collaboration with others, and even more abstract understanding of the Self. The BriSe AI’s conscious understanding of information and flexible adaptation to complex environments are enhanced by positive mutual promotion and support among multiple levels of Self, as well as between Self and learning. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper introduces a new way for machines to think called Brain-inspired and Self-based Artificial Intelligence (BriSe AI). The authors want to make AI more like humans. They think that current AI is not truly intelligent because it doesn’t understand itself or its place in the world. To fix this, they created a special framework that helps AI be more self-aware. This framework has different levels, including how AI sees and learns about the world, how it interacts with its body, and how it works with other machines. The authors hope that this new approach will help create truly intelligent AI. |
