If you’re implementing retrieval augmented generation (RAG), there’s one crucial component you might be missing: a reranking model. While vector similarity search has become the go-to method for retrieving relevant context, relying solely on similarity scores can lead to suboptimal results. Let me show you why reranking is not just an optional enhancement, but a […]
At Vectorize, we want to make it fast and easy for our users to create retrieval-augmented generation (RAG) pipelines to power their AI applications. We’ve tried to make it as intuitive as possible and continue to iterate on our user interface towards this goal. However, when you support dozens of integrations with third-party vector databases, […]
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Imagine all your questions get answered magically. Now replace magic with an algorithm and that’s exactly what AI does. It uses algorithms to provide instant and logical answers to your queries. Of course, you need to be sure that your input is designed to get the right answers. Other than that, it is a mathematical, […]
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