Emily M. Bender — Language Models and Linguistics

In this episode, Emily and Lukas dive into the problems with bigger and bigger language models, the difference between form and meaning, the limits of benchmarks, and why it's important to name the languages we study.Show notes (links to papers and transcript): http://wandb.me/gd-emily-m-bender---Emily M. Bender is a Professor of Linguistics at and Faculty Director of the Master's Program in Computational Linguistics at University of Washington. Her research areas include multilingual grammar engineering, variation (within and across languages), the relationship between linguistics and computational linguistics, and societal issues in NLP.---Timestamps:0:00 Sneak peek, intro1:03 Stochastic Parrots9:57 The societal impact of big language models16:49 How language models can be harmful26:00 The important difference between linguistic form and meaning34:40 The octopus thought experiment42:11 Language acquisition and the future of language models49:47 Why benchmarks are limited54:38 Ways of complementing benchmarks1:01:20 The #BenderRule1:03:50 Language diversity and linguistics1:12:49 Outro

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Gradient Dissent is a machine learning podcast from Weights & Biases with hosts Lukas Biewald, Lavanya Shukla and Caryn Marooney. It takes you behind-the-scenes to learn how industry leaders are putting deep learning models in production at NVIDIA, Meta, Google, Lyft, OpenAI, and more.