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How to Take Control of Your Rag Results

Posted Jul 26, 2024 | Views 170
# RAG
# Quality AI
# Superlinked
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Daniel Svonava
CEO & Co-founder @ Superlinked

Daniel is a Co-founder and CEO of Superlinked - an open-source vector compute framework for building RAG, RecSys, Search & Analytics systems with complex semi-structured data. Superlinked works with Vector Database providers to make it easier to build vector-powered software.

Previously, Daniel was an ML Tech Lead in YouTube Ads infrastructure, building systems that enable the purchase of $10B / year of YouTube Ads.

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SUMMARY

What is the state of the art on RAG quality evaluation? How much attention should you pay to embedding model benchmarks? How to establish and evaluate objectives for your information retrieval system before and after you launch? The journey to Quality AI starts with measurement. The second, third and 100th step are then an iteration and improvement against that measurement - what can we learn from the search & relevance industry that has been around for decades? What challenges are specific to embedding powered retrieval? And how to actually improve your vector search? Let's talk about it!

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TRANSCRIPT

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