Using Vector Databases and Embeddings

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This chapter explores the use of vector databases and embeddings for handling data operations. It discusses the importance of choosing the right embedding model and highlights the challenges and considerations in generating and retrieving data using vector databases.

Recently a16z released a diagram showing the “Emerging Architectures for LLM Applications.” In this episode, we expand on things covered in that diagram to a more general mental model for the new AI app stack. We cover a variety of things from model “middleware” for caching and control to app orchestration.

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