From Arduinos to LLMs: Exploring the Spectrum of ML - MLOps Podcast Episode 162

From Arduinos to LLMs: Exploring the Spectrum of ML - MLOps Podcast Episode 162

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[] LLMs path

13 of 20

13 of 20

[] LLMs path

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From Arduinos to LLMs: Exploring the Spectrum of ML - MLOps Podcast Episode 162

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  1. 1 [] Soham's preferred coffee
  2. 2 [] Takeaways
  3. 3 [] Please share this episode with
  4. 4 [] Soham's background
  5. 5 [] From electrical engineering to Machine Learning
  6. 6 [] Deep learning, Edge Computing, and Quantum Computing
  7. 7 [] Tiny ML
  8. 8 [] Favorite area in Tiny ML chain
  9. 9 [] Applications explored
  10. 10 [] Operational challenges transformation
  11. 11 [] Building with Large Language Models
  12. 12 [] Most Optimal Model
  13. 13 [] LLMs path
  14. 14 [] Prompt engineering
  15. 15 [] Migrating infrastructures to new product
  16. 16 [] Your success where others failed
  17. 17 [] API Accessibility
  18. 18 [] Reality about LLMs
  19. 19 [] Compression angle adds to the bias
  20. 20 [] Wrap up

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