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Speaker "Chandra Khatri" Details Back

 

Topic

Detecting Sensitive Content and Understanding Language in Open-Domain Dialog Systems

Abstract

In this talk, I will go over the problem of detecting Sensitive Content (such as Profanity, Sexism, and Racism) within the language, an extremely challenging problem even for humans. I will describe the Two-stage Large-scale Semi-supervision technique for detecting the sensitive content and showcase how this approach generalizes well across a variety of sensitive classes. Furthermore, task-based Dialog Systems (e.g. most Voice Assistant such as Alexa, Google Assistant) have a well-defined metric associated with the understanding and completion of each task (e.g. "play music", "inform weather", etc.), which is not the case of Open-Domain Dialog Systems due to subjective nature of the problem. In this talk, I will also go over the techniques for Understanding Language in such Dialog Systems.

Profile

Chandra Khatri is one of the leading experts in the field of Conversational AI and Multi-modal AI. Currently, he is the Chief Scientist and Head of AI at Got It AI while also being the CTO of BITSAA Silicon Valley Chapter. He is best known for leveraging cutting edge research and technologies for transforming products thereby impacting hundreds of millions of users. At Got It AI, he is leading the efforts of transforming the AI space by leveraging state-of-the-art technologies in order to deliver Self-Discovering, Self-Training, and Self-Optimizing products. Under his leadership, Got It AI is democratizing Conversational AI and related ecosystems through automation. Prior to Got-It, Chandra was leading various kinds of applied research projects at Uber AI such as Conversational AI, Multi-modal AI, and Recommendation Systems. Prior to Uber AI, he was the founding member of the Alexa Prize Competition at Amazon, wherein he was leading the R&D and got the opportunity to significantly advance the field of Conversational AI, particularly Open-domain Dialog Systems, which is considered as the holy-grail of Conversational AI and is one of the open-ended problems in AI. Prior to Alexa AI, he was driving NLP, Deep Learning, and Recommendation Systems related Applied Research at eBay. He graduated from Georgia Tech with a specialization in Deep Learning in 2015 and holds an undergraduate degree from BITS Pilani, India (2012). His current areas of research include Artificial and General Intelligence, Democratization of AI, Reinforcement Learning, Language Understanding, Conversational AI, Multi-modal and Human-agent Interactions, and Introducing Common Sense within Artificial Agents