#embeddings
3 papers
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inspiration
The Embedding Is Not the Default
Every RAG system encodes text into vectors. The model that produces those vectors — and the dimensionality you accept from it — is an engineering decision. Most engineers make it once, at setup, and never revisit it. That is the wrong posture.
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inspiration
Embeddings Are Not Optional
Every RAG pipeline, semantic search index, and similarity feature runs on embeddings. The generation model gets the credit. The embedding model does the work.
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inspiration
Retrieval Is the Weakest Link
RAG systems fail at retrieval, not generation. Engineers blame the LLM. The problem is upstream.