Join us for technical AI presentations with Q&A, followed immediately by a brief reception with pizza to meet the speaker and address detailed questions. Members of the local academic community are welcome to attend.
Joignez-vous à nous pour des présentations AI technique avec Q&A, suivis immédiatement par une brève réception avec pizza pour rencontrer le conférencier et répondre aux questions détaillées. Les membres de la communauté académique locale sont invités à y assister.
Computational Narrative Intelligence and Story Generation
Mark Riedl, Georgia Tech
Tuesday, April 30, 2019 | Mardi, avril 30 2019
4:30 PM – 6:00 PM EST
Storytelling is a pervasive part of the human experience–we as humans tell stories to communicate, inform, entertain, and educate. In this talk, I will lay out the case for the study of storytelling through the lens of present the case for the study of storytelling through the lens of artificial intelligence and a number of ways computational narrative intelligence can facilitate the creation of intelligent applications that benefit humans and facilitate human-agent interaction. I will explore the grand challenge of building an intelligent system capable of generating fictional stories, including work from my lab using classical artificial intelligence techniques, machine learning, and neural networks.
Dr. Mark Riedl is an Associate Professor in the Georgia Tech School of Interactive Computing and director of the Entertainment Intelligence Lab. Dr. Riedl’s research focuses on human-centered artificial intelligence—the development of artificial intelligence and machine learning technologies that understand and interact with human users in more natural ways. Dr. Riedl’s recent work has focused on story understanding and generation, computational creativity, explainable AI, and teaching virtual agents to behave safely. His research is supported by the NSF, DARPA, ONR, the U.S. Army, U.S. Health and Human Services, Disney, and Google. He is the recipient of a DARPA Young Faculty Award and an NSF CAREER Award.
Learning Healthy Models for Healthcare
Dr. Marzyeh Ghassemi, University of Toronto and Vector Institute
March 25, 2019
4:30 PM – 6:00 PM EST
Health is important, and improvements in health improve lives. However, we still don’t fundamentally understand what it means to be healthy, and the same patient may receive different treatments across different hospitals or clinicians as new evidence is discovered, or individual illness is interpreted.
Health is unlike many success stories in machine learning so far – games like Go and self-driving cars – because we do not have well-defined goals that can be used to learn rules. The nuance of health also requires that we keep machine learning models “healthy” – working to ensure that they do not learn biased rules or detrimental recommendations.
In this talk, Dr. Ghassemi covered some of the many novel technical opportunities for machine learning to tackle that stem from health challenges, and important progress to be made with careful application to domain.