CLC number:
On-line Access: 2022-06-17
Received: 2021-05-04
Revision Accepted: 2022-07-05
Crosschecked: 2021-08-11
Cited: 0
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Citations: Bibtex RefMan EndNote GB/T7714
https://orcid.org/0000-0003-1826-1850
https://orcid.org/0000-0003-0188-5966
Li WEIGANG, Liriam Michi ENAMOTO, Denise Leyi LI, Geraldo Pereira ROCHA FILHO. New directions for artificial intelligence: human, machine, biological, and quantum intelligence[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(6): 984-990.
@article{title="New directions for artificial intelligence: human, machine, biological, and quantum intelligence",
author="Li WEIGANG, Liriam Michi ENAMOTO, Denise Leyi LI, Geraldo Pereira ROCHA FILHO",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="23",
number="6",
pages="984-990",
year="2022",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2100227"
}
%0 Journal Article
%T New directions for artificial intelligence: human, machine, biological, and quantum intelligence
%A Li WEIGANG
%A Liriam Michi ENAMOTO
%A Denise Leyi LI
%A Geraldo Pereira ROCHA FILHO
%J Frontiers of Information Technology & Electronic Engineering
%V 23
%N 6
%P 984-990
%@ 2095-9184
%D 2022
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2100227
TY - JOUR
T1 - New directions for artificial intelligence: human, machine, biological, and quantum intelligence
A1 - Li WEIGANG
A1 - Liriam Michi ENAMOTO
A1 - Denise Leyi LI
A1 - Geraldo Pereira ROCHA FILHO
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 23
IS - 6
SP - 984
EP - 990
%@ 2095-9184
Y1 - 2022
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2100227
Abstract: This comment reviews the “once learning” mechanism (OLM) that was proposed byWeigang (1998), the subsequent success of “one-shot learning” in object categories (Li FF et al., 2003), and “you only look once” (YOLO) in objective detection (Redmon et al., 2016). Upon analyzing the current state of research in artificial intelligence (AI), we propose to divide AI into the following basic theory categories: artificial human intelligence (AHI), artificial machine intelligence (AMI), artificial biological intelligence (ABI), and artificial quantum intelligence (AQI). These can also be considered as the main directions of research and development (R&D) within AI, and distinguished by the following classification standards and methods: (1) human-, machine-, biological-, and quantum-oriented AI R&D; (2) information input processed by dimensionality increase or reduction; (3) the use of one/a few or a large number of samples for knowledge learning.
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