Teaching Machines to Read
For human beings, reading comprehension is a basic task, performed daily. Recently, we see growing interest in Machine Reading Comprehension (MRC) due to potential enterprise applications as well as technological advances including the availability of various MRC datasets like SQUAD, NewsQA, MS MARCO, and others. These datasets have inspired novel, attention-based architectures that can learn sophisticated matching techniques but lack the ability for true comprehension. This talk will provide an overview of the current state-of-the-art for MRC; the limitations preventing widespread usage in real-world applications and the challenges to overcome to progress towards full reading comprehension.
Kaheer is a Principal Research Program Manager at the Microsoft Research Montreal lab. Kaheer co-founded the deep learning for language startup Maluuba and served as its CTO prior to its acquisition, by Microsoft, in early 2017. He currently works on machine learning approaches for natural language processing focusing on question answering, conversation systems and common sense reasoning. I am Principal Research Program Manager at the Microsoft Research Maluuba, Montreal lab. I was one of the co-founders of Maluuba and served as its CTO prior to its acquisition in early 2017. I am interested in machine learning approaches for natural language processing with a focus on question answering, conversation systems and common sense reasoning. Prior to Maluuba, I attended the University of Waterloo where I received a Masters degree in Computer science focusing on information extraction.