Title:
Complexity at Mesoscales: A Common Challenge in Developing Artificial Intelligence
Journal:
Engineering, 2019, 5: 924-929
Authors:
Li Guo, Jun Wu, Jinghai Li*
Abstract:
Exploring the physical mechanisms of complex systems and making effective use of them are the keys to dealing with the complexity of the world. The emergence of big data and the enhancement of computing power, in conjunction with the improvement of optimization algorithms, are leading to the development of artifificial intelligence (AI) driven by deep learning. However, deep learning fails to reveal the underlying logic and physical connotations of the problems being solved. Mesoscience provides a concept to under stand the mechanism of the spatiotemporal multiscale structure of complex systems, and its capability for analyzing complex problems has been validated in different fifields. This paper proposes a research paradigm for AI, which introduces the analytical principles of mesoscience into the design of deep learn ing models. This is done to address the fundamental problem of deep learning models detaching the physical prototype from the problem being solved; the purpose is to promote the sustainable develop ment of AI.
Keywords:
Artificial intelligence, Deep learning, Mesoscience, Mesoscale, Complex system
Link:
