Completed
[] First step of optimizing the prompts
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FrugalGPT: Better Quality and Lower Cost for LLM Applications
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- 1 [] Lingjiao's preferred coffee
- 2 [] Takeaways
- 3 [] Sponsor Ad: Nayur Khan of QuantumBlack
- 4 [] Lingjiao's research at Stanford
- 5 [] Day-to-day research overview
- 6 [] Inventing data management inspired abstractions research
- 7 [] Agnostic Approach to Data Management
- 8 [] Frugal GPT
- 9 [] Just another data provider
- 10 [] Frugal GPT breakdown
- 11 [] First step of optimizing the prompts
- 12 [] Prompt overlap
- 13 [] Query Concatenation
- 14 [] Money saving
- 15 [] Economizing the prompts
- 16 [] Questions to accommodate
- 17 [] LLM Cascade
- 18 [] Frugal GPT saves cost and Improves performance
- 19 [] End-user implementation
- 20 [] Completion Cache
- 21 [] Using a vector store
- 22 [] Wrap up
