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人工智能:科学研究的强大范式。

Artificial intelligence: A powerful paradigm for scientific research.

作者信息

Xu Yongjun, Liu Xin, Cao Xin, Huang Changping, Liu Enke, Qian Sen, Liu Xingchen, Wu Yanjun, Dong Fengliang, Qiu Cheng-Wei, Qiu Junjun, Hua Keqin, Su Wentao, Wu Jian, Xu Huiyu, Han Yong, Fu Chenguang, Yin Zhigang, Liu Miao, Roepman Ronald, Dietmann Sabine, Virta Marko, Kengara Fredrick, Zhang Ze, Zhang Lifu, Zhao Taolan, Dai Ji, Yang Jialiang, Lan Liang, Luo Ming, Liu Zhaofeng, An Tao, Zhang Bin, He Xiao, Cong Shan, Liu Xiaohong, Zhang Wei, Lewis James P, Tiedje James M, Wang Qi, An Zhulin, Wang Fei, Zhang Libo, Huang Tao, Lu Chuan, Cai Zhipeng, Wang Fang, Zhang Jiabao

机构信息

Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.

University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Innovation (Camb). 2021 Oct 28;2(4):100179. doi: 10.1016/j.xinn.2021.100179. eCollection 2021 Nov 28.


DOI:10.1016/j.xinn.2021.100179
PMID:34877560
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8633405/
Abstract

Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.

摘要

人工智能(AI)与计算机科学中著名的有前景的机器学习(ML)技术相结合,正在广泛影响包括科学技术、工业乃至我们日常生活在内的各个领域的许多方面。机器学习技术已经得到发展,用于分析高通量数据,以期获得有用的见解,以新颖的方式进行分类、预测和做出基于证据的决策,这将促进新应用的增长并推动人工智能的持续蓬勃发展。本文对人工智能在基础科学不同方面的发展与应用进行了全面综述,这些基础科学包括信息科学、数学、医学、材料科学、地球科学、生命科学、物理学和化学。详细讨论了各学科所面临的挑战以及人工智能技术应对这些挑战的潜力。此外,我们还阐述了将人工智能融入各学科的新研究趋势。本文旨在为可能融入人工智能的基础科学提供广泛的研究指南,以激励研究人员深入了解基于人工智能的基础科学的最新应用,从而促进这些基础科学的持续发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/1bd92434e300/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/46b9d48e8140/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/79d9c19b98dd/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/10345ae209a6/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/a27ffaa5bb6a/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/d54e373a77e0/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/f0af02164885/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/7e7f33e5dc49/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/5d06a5c424cd/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/0eab48637e81/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/1bd92434e300/gr9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/46b9d48e8140/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/79d9c19b98dd/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/10345ae209a6/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/a27ffaa5bb6a/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/d54e373a77e0/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/f0af02164885/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/7e7f33e5dc49/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/5d06a5c424cd/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/0eab48637e81/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a9d/8633405/1bd92434e300/gr9.jpg

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[2]
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Sci Bull (Beijing). 2021-11-15

[3]
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