Machine learning and deep learning techniques are contributing much to the advancement of science. Their powerful predictive capabilities appear in numerous disciplines, including chaotic dynamics, but they miss understanding. The main thesis here is that prediction and understanding are two very different and important ideas that should guide us about the progress of science. Furthermore, it is emphasized the important role played by that nonlinear dynamical systems for the process of understanding. The path of the future of science will be marked by a constructive dialogue between big data and big theory, without which we cannot understand.

中文翻译：

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科学中的人工智能、混沌、预测和理解

机器学习和深度学习技术为科学进步做出了巨大贡献。他们强大的预测能力出现在许多学科中，包括混沌动力学，但他们没有理解。这里的主要论点是预测和理解是两个非常不同且重要的思想，它们应该指导我们科学的进步。此外，强调了非线性动力系统在理解过程中所起的重要作用。未来科学的道路将以大数据和大理论之间的建设性对话为标志，没有它我们就无法理解。