midLLMOps
What are embeddings in LLMOps?
Updated May 16, 2026
Short answer
Embeddings are dense vector representations of text used for semantic similarity search.
Deep explanation
Embeddings convert text into high-dimensional vectors capturing semantic meaning. Similar texts are placed closer in vector space. They are used in search, clustering, recommendation, and RAG systems.
Real-world example
Search engines finding similar support tickets.
Common mistakes
- Using embeddings for exact keyword matching instead of semantic similarity.
Follow-up questions
- What is cosine similarity?
- Why not use raw text search?