More Language, Less Labeling with Kate Saenko

580

The TWIML AI Podcast
The TWIML AI Podcast
1 min readJun 27, 2022

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About this Episode

Today we continue our CVPR series joined by Kate Saenko, an associate professor at Boston University and a consulting professor for the MIT-IBM Watson AI Lab. In our conversation with Kate, we explore her research in multimodal learning, which she spoke about at the Multimodal Learning and Applications Workshop, one of a whopping 6 workshops she spoke at. We discuss the emergence of multimodal learning, the current research frontier, and Kate’s thoughts on the inherent bias in LLMs and how to deal with it. We also talk through some of the challenges that come up when building out applications, including the cost of labeling, and some of the methods she’s had success with. Finally, we discuss Kate’s perspective on the monopolizing of compute resources for “foundational” models, and her paper Unsupervised Domain Generalization by learning a Bridge Across Domains.

To learn more about this episode, or to access the full resource list, visit twimlai.com/go/580

Originally published at https://twimlai.com on June 27, 2022.

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The TWIML AI Podcast
The TWIML AI Podcast

The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, etc.