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How far have we come in giving our NLU systems common sense?

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Abstract: Commonsense reasoning has been a long-established area in AI for more than three decades. Despite the lack of much ongoing effort in this area after the 80s, recently there has been a renewed interest in the AI community for giving machines common sense, acknowledging it as the holy grail of AI. With the tremendous recent progress in natural language understanding (NLU), the lack of commonsense reasoning capabilities of NLU systems is more evident than ever. In this talk, I’ll discuss the amazing recent progress made in tackling commonsense reasoning benchmarks using the gigantic pre-trained neural models. I’ll talk about the role of benchmarks in measuring our progress and how we can move the goal post. Constructing coherent mental models of narratives that an NLU system reads, through establishing the chain of causality of implicit and explicit events and states, is a promising step forward.

Bio: Nasrin is Co-founder of Verneek, a brand new AI startup that is striving to change the way non-technical people can leverage their ever-growing sources of data. Before Verneek, Nasrin held senior research positions at AI startups BenevolentAI and Elemental Cognition and earlier at Microsoft Research and Google. She received her PhD at the University of Rochester working at the conversational interaction and dialogue research group, with her PhD work focused on commonsense reasoning through the lens of story understanding. She has started lines of research that push AI toward deeper understanding and having common sense, with applications ranging from storytelling to vision & language. She has been a keynote speaker, chair, organizer, and program committee member at different AI venues. Nasrin was named to Forbes’ 30 Under 30 in Science 2019 for her work in AI. Meeting ID: 916 2799 0884 Passcode: 873639

This talk is part of the NLIP Seminar Series series.

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