Abstract

Language understanding has long been a holy grail of Artificial Intelligence, but what exactly constitutes understanding? We argue that while the level of understanding required depends on the task, in many useful NLP applications, the level of understanding required goes beyond what many standard reading comprehension benchmarks are able to assess. We believe that a useful understanding model for many tasks follows from modeling agents, their actions, motivations, and goals, leading to the ability to explain the how and why of certain actions and decisions.

In this talk, I will describe the Natural Learning system we are developing at Elemental Cognition. Our system is designed to continuously read and interact with humans to enhance its knowledge both at the language level and at the domain level. I will discuss and demonstrate how our system learns from users and how it can apply that knowledge to understand new stories.

Biography

Jennifer Chu-Carroll is a research scientist at Elemental Cognition, where she focuses on natural language semantics and dialogue management. Previously, Jennifer was a research staff member and manager at the IBM T.J. Watson Research Center, where her most notable accomplishment was serving as a key technical lead on the Watson project, in which a high-performing question-answering system defeated the two best human players at the game of Jeopardy!, and a member of the technical staff at Lucent Technologies Bell Laboratories focusing on spoken dialogue management. Throughout her career, Jennifer has maintained a strong focus on research and development in natural language processing and related areas. She has published extensively in top conferences and journals and is very engaged in her research community. Jennifer served as general chair of NAACL–HLT 2012, program committee cochair of NAACL–HLT 2006, as area chairs and program committees of many key conferences, and on the editorial boards of multiple journals. She holds a PhD in computer science from the University of Delaware.