Rama Akkiraju
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IBM Fellow,
Director of AI Operations IBM |
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Rama Akkiraju is an IBM Fellow, Master Inventor and IBM Academy Member, and a Director, at IBM’s Watson Division where she leads the AI operations team with a mission to scale AI for Enterprises. Prior to this, Rama led the AI mission of enabling natural, personalized and compassionate conversations between computers and humans. Rama has been named by Forbes as one of the ‘Top 20 Women in AI Research’ in May 2017, has been featured in ‘A-Team in AI’ by Fortune magazine in July 2018 and named ‘Top 10 pioneering women in AI and Machine Learning’ by Enterprise Management 360. In her career, Rama has worked on agent-based decision support systems, electronic market places, and semantic Web services, for which she led a World-Wide-Web (W3C) standard.
Rama has co-authored 4 book chapters, and over 100 technical papers. Rama has 18 issued patents and 25+ pending. She is the recipient of 3 best paper awards in AI and Operations Research. |
Rama holds a Masters degree in Computer Science and has received a gold medal from New York University for her MBA for highest academic excellence. Rama served as the President for ISSIP, a Service Science professional society for 2018 and continues to actively drive AI projects through this professional society.
Technical Vision Talk Abstract: "Polyglot AI: The role of Natural Language Processing (NLP) in Building Multilingual AI Systems"
AI applications are proliferating in consumer and business domains these days around the world. Have you ever wondered how Siri, Google Home, Google Maps or Amazon Echo speaks to users in different countries in their local languages? How does an automated customer support chat bot that you are speaking with or texting with speak or understand your local language to resolve your problems? AI models that power these applications have to speak the language of the user and the language of the business for them to be useful and relevant. Polyglot AI is not magic just the way AI itself is not magic! It takes a lot of hard work to teach AI to understand and speak new languages. In this talk, I’ll take you through some behind the scenes hard work to build multilingual natural language processing systems that enables AI to speak multiple languages.