Faster, Cheaper Retrieval with Embedding Quantization

Embeddings are a fundamental component of most modern AI stack. When working with large document repositories, the computational costs of storing and retrieving embeddings can quickly become prohibitive. Fortunately, there’s a solution: embedding quantization.

What is Embedding Quantization?

Embedding quantization is the process of compressing high-dimensional embedding vectors into a more compact representation such as binary. Instead of storing each number in a 32-bit float, each value is…