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On the cover: The rising in the popularity of big data, artificial intelligence, and simulation technologies has opened up new opportunities for the development of our society. The close integration of real and artificial societies has become a trend, bringing in novel concepts such as parallel society and metaverse. The artificial society system describes, predicts, and guides the real society system, in a closed-loop, iterative, and spiral-rising way, forming a new mode of social operation driven by Data-AI-Simulation techniques. In the future, with the further development of interdisciplinary cooperation and the continuous advancement of technologies, living in metaverse is within reach.
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Position: Home > issue > September 13, 2022 Volume 3, Issue 5
Physics-aware training for the physical machine learning model building
Category:   Commentary   Download:  PDF  Figure  Endnote
Author: Xuecong Sun, Yuzhen Yang, Han Jia, Jun Yang

52.jpg

Schematics of conventional machine learning models and PNN


In recent decades, machine learning has emerged as a very powerful computational method. Because of its exceptional successes in computer science and engineering, machine learning has ignited research interest in other disciplines, including biology, chemistry, physics, and finance. Machine learning models, which are usually regarded as mathematical models, have traditionally been implemented on the basis of digital computing platform (Figure 1A). The increasing prevalence of machine learning has been accompanied by a rapid increase of computing requirements, outpacing Moore¡¯s law.





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