Episode description

Show notes:

- On the Measure of Intelligence by François Chollet - Part 1: Foundations (Paper Explained) [YouTube](https://www.youtube.com/watch?v=3_qGr...)

- [2108.07258 On the Opportunities and Risks of Foundation Models](https://arxiv.org/abs/2108.07258)

- [2005.11401 Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://arxiv.org/abs/2005.11401)

- Negative Data Augmentation: https://arxiv.org/abs/2102.05113

- Beyond Accuracy: Behavioral Testing of NLP models with CheckList: [2005.04118 Beyond Accuracy: Behavioral Testing of NLP models with CheckList](https://arxiv.org/abs/2005.04118)

- Symbolic AI vs Deep Learning battle https://www.technologyreview.com/2020...

- Dense Passage Retrieval for Open-Domain Question Answering https://arxiv.org/abs/2004.04906

- Data Augmentation Can Improve Robustness https://arxiv.org/abs/2111.05328

- Contrastive Loss Explained. Contrastive loss has been used recently… | by Brian Williams | Towards Data Science https://towardsdatascience.com/contra...

- Keras Code examples https://keras.io/examples/

- https://you.com/ -- new web search engine by Richard Socher

- The Book of Why: The New Science of Cause and Effect: Pearl, Judea, Mackenzie, Dana: 9780465097609: Amazon.com: Books https://www.amazon.com/Book-Why-Scien...

- Chelsea Finn: https://twitter.com/chelseabfinn

- Jeff Clune: https://twitter.com/jeffclune

- Michael Bronstein (Geometric Deep Learning): https://twitter.com/mmbronstein https://arxiv.org/abs/2104.13478

- Connor's Twitter: https://twitter.com/CShorten30

- Dmitry's Twitter: https://twitter.com/DmitryKan