CS Events

Faculty Candidate Talk Building Shapeable and Reliable AI with Probabilistic Modeling
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Speaker: Jake Snell

Bio

Jake Snell is a postdoctoral researcher at Princeton University working with Tom Griffiths. He earned his bachelor's degree in Biomedical Engineering at Yale University and his Ph.D. in Computer Science at the University of Toronto, advised by Richard Zemel. His research focuses on integrating deep learning and probabilistic modeling to build AI systems that are more reliable and easier to control. He is a recipient of the Schmidt DataX Postdoctoral Fellowship and finalist for best student paper award at the IEEE International Conference on Image Processing in 2017.

Location : CoRE 301

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Event Type: Faculty Candidate Talk

Abstract: Current LLM architectures are exceedingly powerful yet remain difficult to control while unexpectedly producing harmful outputs such as hallucinations and toxic content. In this talk, I will show how deep learning can borrow the strengths of probabilistic models to address these issues. First, I will show how probabilistic models influence the way that deep neural networks generalize via metalearning. Second, I will demonstrate how probabilistic inference facilitates safe deployment of AI systems in risk-sensitive settings by producing rigorous guarantees about their performance. I will conclude with future directions integrating these lines of work to build deep learning algorithms with capabilities that are verifiable by design.

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Contact  Professor David Pennock

Join Zoom Meeting
https://rutgers.zoom.us/j/2014444359?pwd=WW9ybFNCNVFrUWlycHowSHdNZjhzUT09

Meeting ID: 201 444 4359
Password: 550978