[CMU AI Seminar] November 8 at 12pm (NSH 3305 & Zoom) -- Aditi Raghunathan (CMU) -- Robustness in the era of large pretrained models -- AI Seminar sponsored by SambaNova Systems

[Asher Trockman]

Dear all,

We look forward to seeing you *this coming Tuesday (11/8)* from *1**2:00-1:00
PM (U.S. Eastern time)* for the next talk of this semester's
*CMU AI Seminar*, sponsored by SambaNova Systems <https://sambanova.ai/>.
The seminar will be held in NSH 3305 *with pizza provided *and will be
streamed on Zoom.

To learn more about the seminar series or to see the future schedule,
please visit the seminar website <http://www.cs.cmu.edu/~aiseminar/>.

On 11/8, *Aditi Raghunathan* (CMU) will be giving a talk titled *"**Robustness
in the era of large pretrained models**".*

*Title*: Robustness in the era of large pretrained models

*Talk Abstract*: Machine learning systems often fail catastrophically under
the presence of distribution shift—when the test distribution differs in
some systematic way from the training distribution. This notion of
robustness has remained an open challenge. The past few years have seen the
rise of large models trained on broad data at scale that can be adapted to
several downstream tasks (e.g. BERT, GPT, DALL-E). In this talk, via theory
and experiments, we will discuss how such models open up new avenues, but
also require new techniques for improving robustness.

*Speaker Bio*: Aditi Raghunathan is an assistant professor of computer
science at Carnegie Mellon University. She is interested in building robust
ML systems with guarantees for trustworthy real-world deployment.
Previously, she was a postdoctoral researcher at Berkeley AI Research, and
received her PhD from Stanford University in 2021. Her research has been
recognized by the Arthur Samuel Best Thesis Award at Stanford, a Google PhD
fellowship in machine learning, and an Open Philanthropy AI fellowship.

*In person: *NSH 3305
*Zoom Link*:
https://cmu.zoom.us/j/99510233317?pwd=ZGx4aExNZ1FNaGY4SHI3Qlh0YjNWUT09

Thanks,
Asher Trockman
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