Deep learning has recently become very popular on account of its incredible success in many complex data-driven applications, such as image classification and speech recognition. The database community has worked on data-driven applications for many years, and therefore should be playing a lead role in supporting this new wave. However, databases and deep learning are different in terms of both techniques and applications. In this paper, we discuss research problems at the intersection of the two fields. In particular, we discuss possible improvements for deep learning systems from a database perspective, and analyze database applications that may benefit from deep learning techniques.

中文翻译：

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数据库遇上深度学习：挑战与机遇

深度学习最近变得非常流行，因为它在许多复杂的数据驱动应用程序（例如图像分类和语音识别）中取得了令人难以置信的成功。数据库社区多年来一直致力于数据驱动的应用程序，因此应该在支持这一新浪潮方面发挥主导作用。但是，数据库和深度学习在技术和应用上都不同。在本文中，我们讨论了两个领域交叉点的研究问题。特别是，我们从数据库的角度讨论了深度学习系统的可能改进，并分析了可能受益于深度学习技术的数据库应用程序。