In episode 15 of The Gradient Podcast, we talk to Stanford PhD Candidate Alex Tamkin

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Alex Tamkin is a fourth-year PhD student in Computer Science at Stanford, advised by Noah Goodman and part of the Stanford NLP Group. His research focuses on understanding, building, and controlling pretrained models, especially in domain-general or multimodal settings.

We discuss:

Viewmaker Networks: Learning Views for Unsupervised Representation Learning

DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning

On the Opportunities and Risks of Foundation Models

Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models

Mentoring, teaching and fostering a healthy and inclusive research culture

Scientific communication and breaking down walls between fields

Podcast Theme: “MusicVAE: Trio 16-bar Sample #2” from "MusicVAE: A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music"

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