This is an excerpt. The full article includes a live 2D vector space sandbox — drag a query vector across a semantic coordinate field and watch cosine similarity scores update in real time across 9 framework nodes, with a toggle between Brute Force KNN and HNSW skip-graph traversal modes. Read the full interactive version →
The Geometry of Semantics
In the era of large language models, unstructured text is treated not as raw characters, but as a vector coordinate in a high-dimensional mathematical space.
When you pass text into an embedding model (like Google's text-embedding-004), it maps the semantic meaning into an array of floating-point numbers:
"Redis In-Memory Cache" → [ 0.01249, -0.04581, 0.08914, ..., -0.00312 ] // 3072 dimensions
