Tomas Mikolov is a Senior Researcher at the Czech Institute of Informatics, Robotics, and Cybernetics. His research has covered topics in natural language understanding and representation learning, including Word2Vec, and complexity.

Tomas's PhD thesis is titles "Statistical Language Models Based on Neural Networks", which he completed in 2012 at the Brno University of Technology. We discuss compression and recurrent language models, the backstory behind Word2Vec, and his recent work on complexity & automata.

Episode notes: https://cs.nyu.edu/~welleck/episode25.html

Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html

Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview

[25] Tomas Mikolov - Statistical Language Models Based on Neural Networks

Each episode of The Thesis Review is a conversation centered around a researcher's PhD thesis, giving insight into their history, revisiting older ideas, and providing a valuable perspective on how their research has evolved (or stayed the same) since.