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Articles tagged with #embeddings
Dense retrieval misses keywords. Sparse retrieval misses semantics. Real RAG uses both, fuses the results, and ships a product that finds your product names, error codes, and edge cases.
Your embedding model is probably fine. Your vector store is probably fine. The thing making your RAG retrieval bad is how you chopped your documents up. Three chunking strategies, honest trade-offs.
Everything you actually need to use embeddings in production, in thirty minutes of code. No research papers, no vendor pitches — just the shape of the thing and where it fits in your codebase.
A picture, a sentence, and a song can all be points in the same space. Once that's true, asking 'describe this picture' and 'find a song like this feeling' become the same operation. Here is how.
Pick the one idea that shows up inside every modern AI system — LLMs, recommenders, search, vision. It's this one. Words are points. Images are points. You are a point. Here is why that matters.
Nobody told you where the groups were at the party — but you could see them forming anyway. That's unsupervised learning. Clustering, similarity, and embeddings, told as one story.
