Embeddings
Embeddings turn content into numerical representations that help compare semantic similarity.
The original chunk.
A numerical representation.
Which chunks are closest in meaning?
Search by meaning instead of exact wording
A user can ask “Can I get my money back?” even if the document says “refund eligibility.” Embedding-based retrieval can still surface semantically related chunks.
Embeddings do not make answers automatically correct. They are one part of retrieval, which still depends on good chunks, ranking and source quality.
Quick check
Explain this lesson back in one sentence before continuing. If you cannot, reread the example and key takeaway.
Do not treat vector similarity as proof that a source is authoritative or correct.
Embeddings help retrieval compare meaning. They improve finding relevant context; they do not replace source verification.