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Moin Nadeem (MIT): The extraordinary future of natural language models
Episode 113rd November 2020 • Machine Learning Engineered • Charlie You
00:00:00 01:24:40

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Moin Nadeem is a masters student at MIT, where he studies natural language generation. His research interests broadly include natural language processing, information retrieval, and software systems for machine learning.

Learn more about Moin:

https://moinnadeem.com/

https://twitter.com/moinnadeem

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Timestamps:

01:35 Follow Charlie on Twitter (https://twitter.com/CharlieYouAI)

03:10 How Moin got started in computer science

05:50 Using ML to identify depression on Twitter in high school

11:00 Building a system to track phone locations on MIT’s campus

14:35 Specializing in NLP

17:20 Building an end-to-end fact-checking system (https://www.aclweb.org/anthology/N19-4014/)

25:15 Predicting statement stance with neural multi-task learning (https://www.aclweb.org/anthology/D19-6603/)

27:20 Is feature engineering in NLP dead?

29:40 Reconciling language models with existing knowledge graphs

35:20 How advances in AI hardware will affect NLP research (crazy!)

47:25 Moin’s research into sampling algorithms for natural language generation (https://arxiv.org/abs/2009.07243)

57:10 Under-rated areas of ML research

01:00:10 How research works at MIT CSAIL

01:04:35 How Moin keeps up in such a fast-moving field

01:11:30 Starting the MIT Machine Intelligence Community

01:16:30 Rapid Fire Questions


Links:

FAKTA: An Automatic End-to-End Fact Checking System

StereoSet: Measuring stereotypical bias in pretrained language models

Neural Multi-Task Learning for Stance Prediction

Rich Sutton - The Bitter Lesson

A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation

Strategies for Pre-training Graph Neural Networks

Transformers For Image Recognition at Scale

Cerebras CS-1

Klarity: AI for Law Contract Review

Jacob Andreas

Jure Leskovec

Shoe Dog

Hamilton

Becoming

Mindset

The Innovators

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