newsletter/2021/13 (Link Bibliography)

“newsletter/​2021/​13” links:

  1. https://www.gwern.net/newsletter/2021/13

  2. https://gwern.substack.com

  3. https://www.gwern.net/tags/newsletter

  4. https://www.gwern.net/newsletter/2021/01

  5. https://www.gwern.net/newsletter/2021/02

  6. https://www.gwern.net/newsletter/2021/03

  7. https://www.gwern.net/newsletter/2021/04

  8. https://www.gwern.net/newsletter/2021/05

  9. https://www.gwern.net/newsletter/2021/06

  10. https://www.gwern.net/newsletter/2021/07

  11. https://www.gwern.net/newsletter/2021/08

  12. https://www.gwern.net/newsletter/2021/09

  13. https://www.gwern.net/newsletter/2021/10

  14. https://www.gwern.net/newsletter/2021/11

  15. https://www.gwern.net/newsletter/2021/12

  16. https://www.gwern.net/newsletter/2020/13

  17. https://www.gwern.net/newsletter/2019/13

  18. https://www.gwern.net/newsletter/2018/13

  19. https://www.gwern.net/newsletter/2017/13

  20. https://www.gwern.net/newsletter/2016/13

  21. https://www.gwern.net/newsletter/2015/13

  22. https://www.gwern.net/Changelog#2021

  23. ⁠, Gwern Branwen (2020-10-30):

    Subreddit for discussing AI, machine learning, or deep learning approaches involving big numbers: billions of parameters, millions of n, petaflops, etc. eg ⁠. Most research is conducted at much smaller scale; this subreddit is for research analogous to ‘high energy physics’, requiring specialized approaches, large investments, consortium, etc.

    Topics: How? Who? Why do they work? What are they good for? What resources are available? Who will pay & how? What is the future of such approaches? What global consequences will there be?