Knowledge and memory
How to give a model the knowledge it needs, and how an agent remembers what matters between sessions: chunking documents, embeddings and keyword search, reranking, agentic RAG, knowledge graphs, long-term memory — what to remember, how to update it and how to forget.
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01The whole topic
Take the whole "Knowledge and memory" topic
Every question of the topic — one per fact, from easy to hard. An honest check of the whole topic rather than of a single section.
02
Topic sections
#QUIZQUESTIONSDIFFICULTYSTATUS
2.2Hybrid search and rerankingWhy hybrid search is needed, Blind spots of the two kinds of search, The hybrid search pipeline
2.3Query rewriting and contextual retrievalA query without context, Rewriting with entity resolution, The step-back technique
2.5Knowledge graphs and GraphRAGWhere GraphRAG beats vector RAG, Strengths of a knowledge graph, Limits of a graph as a memory store
2.6Organizing and updating knowledgeWhy "naive" RAG falls short, A knowledge base in files, Updating knowledge as a pull request
2.7Long-term agent memoryWhat to extract into memory, Levels of memory capability, Memory storage formats