Data synthesis for SOTA LLMs

Practical AI: Machine Learning, Data Science, LLM

Nous Research has been pumping out some of the best open access LLMs using SOTA data synthesis techniques. Their Hermes family of models is incredibly popular! In this episode, Karan from Nous talks about the origins of Nous as a distributed collective of LLM researchers. We also get into fine-tuning strategies and why data synthesis works so well.

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Sponsors:

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Featuring:

• Karan Malhotra – LinkedIn
• Chris Benson – Twitter, GitHub, LinkedIn, Website
• Daniel Whitenack – Twitter, GitHub, Website

Show Notes:

• Nous on Hugging Face
• Nous Research

Something missing or broken? PRs welcome!

챕터

1. Welcome to Practical AI (Dance Party!) (00:00:00)

https://changelog.com/beats/dance-party

2. Karan Malhotra (00:00:43)

3. Origins of Nous Research (00:01:57)

4. What is synthetic data (00:10:24)

5. Effects of model licensing (00:16:47)

6. Map of Nous (00:22:23)

7. How is Nous organized? (00:26:45)

8. Sponsor: Read Write Own (00:30:41)

https://readwriteown.com/?utm_source=changelog&utm_medium=practicalai&utm_campaign=changelog

9. Fine Tuning advice (00:31:48)

10. Stuff to look for (00:35:00)

11. What's next? (00:40:45)

12. Thank you! (00:45:03)

13. Outro (Dance Party!) (00:46:00)

https://changelog.com/beats/dance-party