's Heroes of Deep Learning: Dawn Song

Dawn Song is well-known for her research on the intersection of deep learning and security. Aside from her research, Song is also a Professor in the Department of Electrical Engineering and Computer Science at UC Berkeley and CEO of Oasis Labs, a blockchain startup that is creating a privacy-first cloud computing platform no blockchain. She has received several awards for her work including the MacArthur Fellowship, the Guggenheim Fellowship, and Best Paper awards from top conferences.

Andrew sits down with Song to chat about her unconventional career path and her current research projects.

Here’s what you’ll learn in the interview:

00:34: How Song first got started in deep learning and security
4:00: How Song self-designed a reading program structured around representational learning
13:22: How computer security can help deep learning
17:03: Song’s research on how to build resilient machine learning systems
21:55 How a “consistency check” approach can defend against attacks
25:31: Song’s work in AI and data privacy
27:49: How deep learning can help computer security
30:16: How Song’s startup, Oasis Labs, is creating privacy-preserving smart contracts
34:42: Song’s advice for learners breaking into a new field

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