Commonsense AI: Myth and Truth
Yejin Choi
2021 Invited Talk
Abstract
Despite considerable advances in deep learning, AI remains to be narrow and brittle. One fundamental limitation is its lack of commonsense intelligence: trivial for humans, but mysteriously hard for machines. In this talk, I'll discuss the myth and truth about commonsense AI---the blend between symbolic and neural knowledge, the continuum between knowledge and reasoning, and the interplay between reasoning and language generation
Speaker
Yejin Choi
Yejin Choi is the Dieter Schwarz Foundation Professor and Senior Fellow at Stanford's Computer Science and Institute for Human-Centered AI (HAI). She is a MacArthur Fellow, AI2050 Senior Fellow, and named to Time100 Most Influential People in AI (2023, 2025). Choi has received 2 Test-of-Time Awards and 10 Best/Outstanding Paper Awards at top AI conferences including ACL, ICML, NeurIPS, ICCV, CVPR, and AAAI. She was a main stage speaker at TED 2023 and has delivered keynotes at several AI conferences including NeurIPS, ICLR, CVPR, ACL, AAAI, MLSys, VLDB, and WebConf. She has also won the Borg Early Career Award (BECA) in 2018, the inaugural Alexa Prize Challenge in 2017, and IEEE AI’s 10 to Watch in 2016. Her research focuses on democratizing generative AI through smaller yet powerful language models, scaling intelligence via smarter algorithms, alternative training recipes of language models, pluralistic alignment, and AI for science and social good. She consults at NVIDIA, and was was previously Professor at UW and Senior Director at AI2. She received her Ph.D. in Computer Science at Cornell University and BS in Computer Engineering at Seoul National University in Korea.
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