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[] Generative AI safety nets
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Classroom Contents
Python Power: How Daft Embeds Models and Revolutionizes Data Processing - Podcast 165
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- 1 [] Sammy's preferred coffee
- 2 [] Takeaways
- 3 [] Please like, share, and subscribe to our MLOps channels!
- 4 [] California Raisins
- 5 [] Getting into complex data
- 6 [] Autopilot
- 7 [] Autopilot challenges
- 8 [] Shrinking Mega models
- 9 [] Architecting ML on tinyML
- 10 [] Cutting through regulation
- 11 [] Creation of Daft
- 12 [] Daft dealing with complex data
- 13 [] Easy query
- 14 [] Eventual
- 15 [] Fitting into the LLMs world
- 16 [] Chain of Thought for LLMs
- 17 [] Providing a SQL engine for LLMS today
- 18 [] Daft's take off prior to LLMS
- 19 [] Querying MLOps community podcasts
- 20 [] Takeaways from tinyML
- 21 [] Haystack type queries
- 22 [] Generative AI safety nets
- 23 [] Tying in with Daft
- 24 [] Tabular data vs unstructured or complex data needs and trade-offs
- 25 [] Toolkit for System Building
- 26 [] Tiny ML with Daft optimization
- 27 [] Out-of-the-box capability
- 28 [] Workaround
- 29 [] Open source big assumption
- 30 [] Open source 2 years behind
- 31 [] Sammy's success
- 32 [] Wrap up
