#Embedding
3 related articles
·4 min
Why Your 0.8 Similarity Threshold Breaks After Switching Embedding Models
RAG bot answering "I don't know" after an embedding model swap? The root cause is anisotropy and contrastive training making cosine similarity scores model-specific. Learn to measure noise floors, calibrate thresholds, and use rerankers.
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·2 min
Getting Started with RAG Knowledge Bases: From Vector Retrieval to Embedding Models Explained
A beginner's guide to building RAG knowledge bases — covering vector retrieval, context assembly, Embedding models, and why model consistency is critical for accurate semantic search.
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·2 min
Embedding Models in RAG Explained: From Knowledge Base Construction to Similarity Retrieval
A deep dive into how Embedding models power RAG: from chunking knowledge bases and storing vectors, to retrieving top-k documents and assembling prompts — and why fine-tuning Embeddings is key.
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