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The Production Reality: Why Cosine Similarity Often Wins Anyway [Part 3/3]
In the final part of my series, we leave theory behind and face production reality. While normalizing L2 Distance is mathematically possible, it's often fragile and complex in live systems.The reason?...
How to Actually Interpret L2 Distance Results [Part 2/3]
Cosine Similarity has a clean, intuitive range from -1 to +1. But L2 Distance? It goes from 0 to infinity—so how do you actually interpret it?In Part 2 of my series on similarity metrics for RAG syste...
Why Cosine Similarity > L2 Distance for RAG Systems (usually) [Part 1/3]
Similarity isn’t one-size-fits-all.In RAG systems, choosing between Cosine Similarity and L2 Distance affects what gets retrieved—and whether it's actually relevant.This post breaks down the differenc...
Unlocking the Power of Retrieval-Augmented Generation (RAG) in AI: A Game Changer for SAP Customers
Discover how RAG framework combines large language models with real-time data retrieval to provide businesses with accurate, grounded insights. Don’t miss this deep dive into the future of AI with SAP...
Building an End-to-End RAG Application Using FastAPI on BTP Cloud Foundry
IntroductionRetrieval-Augmented Generation (RAG) applications significantly enhance the contextual relevance of large language model (LLM) outputs by integrating real-time database lookups. This tutor...
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