The Gradient
The Gradient: Perspectives on AI
Christopher Manning: Linguistics and the Development of NLP

Christopher Manning: Linguistics and the Development of NLP

A conversation with Christopher Manning, Director of the Stanford AI Lab.

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In episode 41 of The Gradient Podcast, Daniel Bashir speaks to Christopher Manning.

Chris is the Director of the Stanford AI Lab and an Associate Director of the Stanford Human-Centered Artificial Intelligence Institute. He is an ACM Fellow, an AAAI Fellow, and past President of ACL. His work currently focuses on applying deep learning to natural language processing; it has included tree recursive neural networks, GloVe, neural machine translation, and computational linguistic approaches to parsing, among other topics. 

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  • (00:00) Intro

  • (02:40) Chris’s path to AI through computational linguistics

  • (06:10) Human language acquisition vs. ML systems

  • (09:20) Grounding language in the physical world, multimodality and DALL-E 2 vs. Imagen

  • (26:15) Chris’s Linguistics PhD, splitting time between Stanford and Xerox PARC, corpus-based empirical NLP

  • (34:45) Rationalist and Empiricist schools in linguistics, Chris’s work in 1990s

  • (45:30) GloVe and Attention-based Neural Machine Translation, global and local context in language

  • (50:30) Different Neural Architectures for Language, Chris’s work in the 2010s

  • (58:00) Large-scale Pretraining, learning to predict the next word helps you learn about the world

  • (1:00:00) mBERT’s Internal Representations vs. Universal Dependencies Taxonomy

  • (1:01:30) The Need for Inductive Priors for Language Systems

  • (1:05:55) Courage in Chris’s Research Career

  • (1:10:50) Outro (yes Daniel does have a new outro with ~ music ~)


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The Gradient
The Gradient: Perspectives on AI
Deeply researched, technical interviews with experts thinking about AI and technology. Hosted, recorded, researched, and produced by Daniel Bashir.