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- RAG
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Classroom Contents
Understanding Generative AI: RAG, Semantic Search, Embeddings, and Vectors
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- 1 - Introduction
- 2 - My typical day and need for information
- 3 - RAG
- 4 - LLM refresher
- 5 - Orchestrators and information to LLMs
- 6 - Semantic index, search, vector, embeddings?
- 7 - Embedding models and creating vector
- 8 - 2 dimensions
- 9 - Semantic search and nearest neighbor
- 10 - Why embeddings and semantic search are so important
- 11 - Summary and close
