Vector Spacesmath
A set of vectors closed under addition and scalar multiplication, with notions of basis, dimension, and norm.
Embeddings are points in a high-dimensional vector space; distance and angle there encode semantic relations.
Where it appears
- SKCE foundation for embeddings and vector-search
Descend
Prerequisites
Dependencies
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Foundations
Historical evolution
Hilbert spaces formalized infinite-dimensional analogs; the setting for all embedding geometry.
Implementation details
Embedding dimension (1536 in upstream OpenAI, 256 after random-projection reduction).
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