What it is
An embedding maps text (or images, audio, etc.) into a numeric vector space where "similar meaning" tends to be closer together.
Where you use them
- Semantic search
- Clustering and deduplication
- Retrieval-augmented generation (RAG)
Gotchas
- Embedding quality depends on the model and your data.
- Similarity metrics (cosine, dot product) matter.