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I built a RAG system that queries 36M+ vectors in <0.03 seconds.
The technique used makes RAG 32x memory efficient!
Check the detailed breakdown with code below:
4.8. klo 14.33
A simple technique makes RAG ~32x memory efficient!
- Perplexity uses it in its search index
- Azure uses it in its search pipeline
- HubSpot uses it in its AI assistant
Let's understand how to use it in RAG systems (with code):
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