Home > Events > CLIP Colloquium: Yejin Choi (UW)
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CLIP Colloquium: Yejin Choi (UW)

Time: 
Tuesday, October 27, 2020 - 1:00 PM to 2:00 PM
Location: 
Virtual - https://umd.zoom.us/j/97647463145?pwd=UlQrQ0ttRHIyd3RCN0Vta01SdkJKdz09

 

Commonsense Intelligence: Cracking the Longstanding Challenge in AI

Abstract: Despite considerable advances in deep learning, AI remains to be narrow and brittle. One fundamental limitation is its lack of common sense: intuitive reasoning about everyday situations and events, which in turn, requires a wide spectrum of commonsense knowledge about how the physical and social world works, ranging from naive physics to folk psychology to ethical norms. In this talk, I will share our recent adventures in modeling neuro-symbolic commonsense models by melding symbolic and declarative knowledge stored in large-scale commonsense graphs with neural and implicit knowledge stored in large-scale neural language models. I will conclude the talk by discussing major open research questions, including the importance of algorithmic solutions to reduce incidental biases in data that can lead to overestimation of true AI capabilities.
 
Bio: Yejin Choi is a Brett Helsel associate professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington and also a senior research manager at AI2 overseeing the project Mosaic. Her research interests include commonsense knowledge and reasoning, neural language (de-)generation, language grounding, and AI for social good. She is a co-recipient of the AAAI Outstanding Paper Award in 2020, Borg Early Career Award (BECA) in 2018, IEEE’s AI Top 10 to Watch in 2015, the ICCV Marr Prize in 2013, and the inaugural Alexa Prize Challenge in 2017. She received her Ph.D. in Computer Science from Cornell University.