Each word becomes a vector (BGE-M3, local) and we project 1024 dimensions to 2D (PCA). Semantically close words land near each other - a car near a truck, a language near a language.
Embeddings are local (BGE-M3), PCA-projected to 2D. Near = semantically close. No storage.
Sample word sets: