论文标题
人工智能，混乱，科学中的预测和理解
Artificial Intelligence, Chaos, Prediction and Understanding in Science
论文作者
论文摘要
机器学习和深度学习技术为科学的发展做出了很大的贡献。它们强大的预测能力出现在包括混乱动态在内的许多学科中，但他们错过了理解。这里的主要论点是，预测和理解是两个截然不同且重要的思想，应该指导我们有关科学进步。此外，它强调了非线性动力学系统在理解过程中起着重要的作用。科学未来的道路将以大数据与大理论之间的建设性对话为标志，没有我们就无法理解。
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.
