Why OpenAI Embeddings Still Work Even After You Truncate Them

Why do OpenAI embeddings still work even after you truncate a large number of dimensions? In this video, we explore Matryoshka Representation Learning (MRL), a training technique that allows embeddings to remain useful even when you use only a prefix of the full vector. This makes it possible to trade off accuracy, memory usage, and retrieval latency at inference time. We first look at how embeddings are normally trained using contrastive learning, and why standard embedding models do not guarantee that truncated vectors will work well. Then we see how Matryoshka Representation Learning modif…