When brain-inspired AI meets AGI
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 intelligen...
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| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2023-06-01
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| Series: | Meta-Radiology |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S295016282300005X |
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| _version_ | 1846170036923793408 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Lin Zhao |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-b9c0434f29744736bf57199644f5db5c |
| institution | Kabale University |
| issn | 2950-1628 |
| language | English |
| publishDate | 2023-06-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Meta-Radiology |
| spelling | doaj-art-b9c0434f29744736bf57199644f5db5c2024-11-12T05:22:35ZengKeAi Communications Co., Ltd.Meta-Radiology2950-16282023-06-0111100005When brain-inspired AI meets AGILin Zhao0Lu Zhang1Zihao Wu2Yuzhong Chen3Haixing Dai4Xiaowei Yu5Zhengliang Liu6Tuo Zhang7Xintao Hu8Xi Jiang9Xiang Li10Dajiang Zhu11Dinggang Shen12Tianming Liu13School of Computing, The University of Georgia, Athens 30602, USADepartment of Computer Science and Engineering, The University of Texas at Arlington, Arlington 76019, USASchool of Computing, The University of Georgia, Athens 30602, USAMOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Computing, The University of Georgia, Athens 30602, USADepartment of Computer Science and Engineering, The University of Texas at Arlington, Arlington 76019, USASchool of Computing, The University of Georgia, Athens 30602, USASchool of Automation, Northwestern Polytechnical University, Xi'an 710072, ChinaSchool of Automation, Northwestern Polytechnical University, Xi'an 710072, ChinaMOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, ChinaDepartment of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston 02115, USADepartment of Computer Science and Engineering, The University of Texas at Arlington, Arlington 76019, USASchool of Biomedical Engineering, ShanghaiTech University, Shanghai 201210, China; Shanghai United Imaging Intelligence Co., Ltd., Shanghai 200230, China; Shanghai Clinical Research and Trial Center, Shanghai, 201210, ChinaSchool of Computing, The University of Georgia, Athens 30602, USA; Corresponding author.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.http://www.sciencedirect.com/science/article/pii/S295016282300005X |
| spellingShingle | 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 When brain-inspired AI meets AGI Meta-Radiology |
| title | When brain-inspired AI meets AGI |
| title_full | When brain-inspired AI meets AGI |
| title_fullStr | When brain-inspired AI meets AGI |
| title_full_unstemmed | When brain-inspired AI meets AGI |
| title_short | When brain-inspired AI meets AGI |
| title_sort | when brain inspired ai meets agi |
| url | http://www.sciencedirect.com/science/article/pii/S295016282300005X |
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