Building Machine Learning Systems that Understand

Abstract

Over the past five years, deep learning and large-scale neural networks have made significant advances in speech recognition, computer vision, language understanding and translation, robotics, and many other fields. Deep learning allows the use of very raw forms of data in order to build higher-level understanding of data automatically, and can also be used to learn to accomplish complex tasks. In the next decade, it is likely that a fruitful direction for research in data management will be in how to seamlessly integrate these kinds of machine learning models into systems that store and manage data. In this talk, I will highlight some of the advances that have been made in deep learning and suggest some interesting directions for future research.