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Presentation: Lessons Developing Conversational AI Interfaces

Track: Solving Software Engineering Problems with Machine Learning

Location: Cyril Magnin III

Duration: 1:40pm - 2:20pm

Day of week: Wednesday

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Abstract

This talk will cover building conversational AI using deep learning technologies and lessons learnt in developing conversational interfaces. The first part of the talk will describe recent advances in deep learning that has led to tremendous progress in natural language processing and is making conversational AI a reality. Conversational AI includes intent classification, sequence labeling, understanding dialogs and context, and coming up with responses to users messages. The second part of the talk will address lessons learned developing conversational interfaces. A conversational interface needs to be personable in addressing, adaptive in understanding, and available with many different supported tasks. Overall, key take aways from the talk will be better understanding of (1) deep learning techniques for natural language processing and (2) interaction patterns for building a good conversational interface.

Speaker: Mitul Tiwari

Cofounder and CTO of @PassageAI

Mitul Tiwari is the CTO and Co-founder of Passage.AI. His expertise lies in building data-driven products using AI, Machine Learning and big data technologies. Previously he was head of People You May Know and Growth Relevance at LinkedIn, where he led technical innovations in large-scale social recommender systems. Prior to that, he worked at Kosmix (now Walmart Labs) on web-scale document and query categorization, and its applications. He earned his PhD in Computer Science from the University of Texas at Austin and his undergraduate degree from the Indian Institute of Technology, Bombay. He has also co-authored more than twenty publications in top conferences such as KDD, WWW, RecSys, VLDB, SIGIR, CIKM, and SPAA.

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