Binary Quantization: Make RAG 32x More Memory-Efficient

How to make RAG 32x more memory-efficient 😨

There’s a simple technique, widely used in the industry, that makes RAG about 32x more memory-efficient.

Perplexity uses it in its search index. Azure uses it in its search pipeline. HubSpot uses it in its AI assistant.

To understand it, here’s a guide where you’ll build a RAG system that queries 36M+ vectors in <30 ms.

And the technique that makes this possible is called binary quantization.