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On-line Access: 2023-08-29

Received: 2022-12-31

Revision Accepted: 2023-04-18

Crosschecked: 2023-08-29

Cited: 0

Clicked: 1011

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yingbo LI

https://orcid.org/0000-0003-3933-4342

Yucong DUAN

https://orcid.org/0000-0001-8417-892X

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Frontiers of Information Technology & Electronic Engineering  2023 Vol.24 No.8 P.1231-1238

http://doi.org/10.1631/FITEE.2200675


Physical artificial intelligence (PAI): the next-generation artificial intelligence


Author(s):  Yingbo LI, Zhao LI, Yucong DUAN, Anamaria-Beatrice SPULBER

Affiliation(s):  School of Computer Science and Technology, Hainan University, Haikou 570228, China; more

Corresponding email(s):   xslwen@outlook.com, lzjoey@gmail.com, duanyucong@hotmail.com

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Yingbo LI, Zhao LI, Yucong DUAN, Anamaria-Beatrice SPULBER. Physical artificial intelligence (PAI): the next-generation artificial intelligence[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(8): 1231-1238.

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Abstract: 
Artificial intelligence (AI) has been a driving force for innovation and social progress in various domains (Pan, 2017). However, most of its industrial applications have focused on the signal processing domain, which relies on data generated and collected by different sensors. Recently, some researchers have suggested combining digital AI (DIAI) and physical AI (PAI), which could lead to a significant advancement in the theoretical foundation of AI. In this paper, we explore the concept of PAI and propose two subdomains: integrated PAI (IPAI) and distributed PAI (DPAI). We also discuss the challenges and opportunities for the sustainable development and governance of PAI. Since PAI requires continuous processing of signals from distributed sources across the edge, fog, and Internet of Things (IoT), it can be seen as an extension of the distributed computing continuum system in the field of AI.

物理人工智能:下一代人工智能

李颖博1,李朝2,段玉聪1,Anamaria-Beatrice SPULBER1
1海南大学计算机科学与技术学院,中国海口市,570228
2之江实验室,中国杭州市,311121
摘要:人工智能(AI)已经成为各领域创新和社会进步的驱动力。然而,其大多数工业应用集中在信号处理领域,这依赖于不同传感器产生和收集的数据。最近,一些研究人员提出将数字人工智能和物理人工智能结合,这可能带来人工智能理论基础的重大进步。在本文中,我们探讨了物理人工智能的概念并提出两个子领域:集成式物理人工智能和分布式物理人工智能。我们还讨论了物理人工智能可持续发展和治理所面临的挑战和机遇。由于物理人工智能需要连续处理来自边缘、雾和物联网的分布式信号,它可以被看作分布式计算连续系统在人工智能领域的延伸。

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