AI trends: a Latent Space crossover

Practical AI

Daniel had the chance to sit down with @swyx and Alessio from the Latent Space pod in SF to talk about current AI trends and to highlight some key learnings from past episodes. The discussion covers open access LLMs, smol models, model controls, prompt engineering, and LLMOps. This mashup is magical. Don’t miss it!

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Featuring:

• Shawn Wang – Website, GitHub, X
• Alessio Fanelli – Website, GitHub, X
• Daniel Whitenack – Website, GitHub, X

Show Notes:

• Latent Space podcast
• Featured Latent Space episodes:
  • Benchmarks
  • Reza Shabani
  • MosaicML and MPT
  • Segment Anything
  • Mike Conover
• Featured Practical AI episodes:
  • From notebooks to Netflix scale with Metaflow
  • Capabilities of LLMs 🤯
  • ML at small organizations
• Prediction Guard
• Data Dan

Something missing or broken? PRs welcome!

챕터

1. Welcome to Practical AI (00:00:00)

2. Latent Space Podcast (00:01:16)

3. Practical AI Podcast (00:04:00)

4. Prediction Guard (00:06:20)

5. Daniel's favorite episodes (00:08:05)

6. Alessio's favorite episode (00:10:21)

7. Swyx's favorite episode (00:10:54)

8. Listener favorites (00:12:44)

9. LLMOps (00:15:14)

10. Reza Shabani (00:17:06)

11. Benchmarks 101 (00:19:06)

12. Roboflow (00:20:06)

13. Mode collapse (00:21:38)

14. Rajiv Shah (00:26:21)

15. Staying on top of things (00:28:01)

16. Kirsten Lum (00:33:11)

17. datadan.io (00:34:31)

18. Prompt engineering (00:38:48)

19. Unique challenges engineers face (00:40:38)

20. AI-UX (00:42:51)

21. NLP data sets (00:45:31)

22. Unlabeled data sets (00:50:49)

23. Lightning round! (00:55:07)

24. What's already happened in AI? (00:55:20)

25. Unsolved questions in AI (00:56:27)

26. Get hands on (00:58:01)

27. Outro (00:58:53)