Vector Searchconcept
Retrieval that ranks items by vector similarity (typically approximate nearest neighbor) rather than keyword match.
Embeddings make vector search the natural retrieval primitive for semantic queries; it underpins RAG and clustering.
Where it appears
- SKCE foundation for rag
- embeddings
- clustering
Descend
Prerequisites
Dependencies
- —
Foundations
Historical evolution
ANN indexes (HNSW, IVF) made billion-scale vector search practical.
Implementation details
SKCE's explorer does NOT do live vector search; the curriculum's search is a pre-built inverted index (compile-time, not runtime).
Sources
- [2026-07-11-knowledge-compiler-compiling-human-knowledge-into-static-semantic-artifacts] 2026-07-11-knowledge-compiler-compiling-human-knowledge-into-static-semantic-artifacts
- [2026-07-11-knowledge-compiler-compiling-human-knowledge-into-static-semantic-artifacts] 2026-07-11-knowledge-compiler-compiling-human-knowledge-into-static-semantic-artifacts