Embedding Model
A specialized neural network designed to convert text, images, or audio into dense numerical vectors that capture the underlying semantic meaning of the data.
Think of It Like This
Like translating a library of books into a universal mathematical language where books with similar themes are placed right next to each other.
Embedding models are the backbone of modern search and retrieval systems. They project inputs into a high-dimensional latent space where geometric distance correlates with semantic similarity. These representations allow algorithms to perform semantic search, clustering, and classification much more effectively than exact keyword matching.