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Tagged: Vector Search
Improving RAG Answers One Measured Change at a Time
A measure-first workflow for fixing weak RAG answers: tune chunking, top_k, reranking, hybrid search and query rewriting one at a time and track retrieval metrics.
4 min readChoosing and Tuning Embedding Models for Production RAG Systems
Learn how embedding models turn text into searchable vectors, why domain vocabulary breaks semantic search, and how to select, compress, and fine-tune models for production RAG.
29 min readReducing Hallucinations in a Medical RAG Chatbot Pipeline
Cutting hallucinations in a medical RAG chatbot with hybrid search, reranking and a strict refuse-to-fabricate policy, after plain vector search fell short.
9 min readA Tiered Map of AI Engineering Concepts and When They Matter
AI engineering concepts in three tiers: the six that decide whether an LLM system works, the ones RAG and vector search need in production, and what can wait.
11 min read
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