Author Interview - Memory-Assisted Prompt Editing to Improve GPT-3 After Deployment

Author Interview - Memory-Assisted Prompt Editing to Improve GPT-3 After Deployment

Yannic Kilcher via YouTube Direct link

- Intro

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1 of 16

- Intro

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Author Interview - Memory-Assisted Prompt Editing to Improve GPT-3 After Deployment

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  1. 1 - Intro
  2. 2 - Paper Overview
  3. 3 - What was your original motivation?
  4. 4 - There is an updated version of the paper!
  5. 5 - Have you studied this on real-world users?
  6. 6 - How does model size play into providing feedback?
  7. 7 - Can this be used for personalization?
  8. 8 - Discussing experimental results
  9. 9 - Can this be paired with recommender systems?
  10. 10 - What are obvious next steps to make the system more powerful?
  11. 11 - Clarifying the baseline methods
  12. 12 - Exploring cross-lingual customization
  13. 13 - Where did the idea for the clarification prompt come from?
  14. 14 - What did not work out during this project?
  15. 15 - What did you learn about interacting with large models?
  16. 16 - Final thoughts

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