Event Description

Selected as the National AI Institute for Foundations of Machine Learning (IFML) by the National Science Foundation (NSF) in 2020, we are partnering with the Texas Advanced Computing Center (TACC) to widen the knowledge and teaching of Machine Learning and AI in High Schools. 

Presented by Raymond Mooney.

Computers that can understand and communicate in human language is a foundational goal of AI and has many applications that are increasingly impacting our everyday lives. This includes systems that recommend news and entertainment, engage in task-oriented or chit-chat conversations (e.g. Siri and Alexa), filter spam from email, fact-check on-line information, and translate from one language to another. This talk will review AI work on these and other natural language applications and discuss relevant ethical issues on their societal impacts.

Ray Mooney is a Professor in the Department of Computer Science at The University of Texas at Austin (UT). He wrote his first essay on Artificial Intelligence in high school in 1979, then received his B.S., M.S. and Ph.D. all from the University of Illinois at Urbana-Champaign before joining the UT faculty in 1988.  His research has been primarily in Machine Learning and Natural Language Processing, and his recent work has focused on language understanding for commanding and teaching robots and making AI systems that can explain their reasoning to human users.

Logistics

A Zoom link will be sent to registrants prior to the webinar.

Schedule

Monday, June 28, 2021

10:00-11:00am Central Time

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You can view the full list of webinars and recordings on our AI / ML Webinar Series page at https://utakeit.tacc.utexas.edu/r/AI_ML_webinars_2021/ 

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About the Institute for Foundations of Machine Learning - a National AI Research Institute

Designated by the National Science Foundation (NSF) in 2020, we are the National AI Institute for Foundations of Machine Learning (IFML). We develop the key foundational tools for the next decade of AI innovation leveraging the combined forces of The University of Texas at Austin, University of Washington, Wichita State University, and Microsoft Research. Our researchers create new algorithms that can help machines learn on the fly, change their expectations as they encounter people and objects in real life, and even bounce back from deliberate attempts by adversaries to manipulate datasets.

This program is supported by the National Science Foundation Award FAIN 2019844.