Dense Vectors
The semantic meaning representations that let AI search understand concepts rather than just matching words.
Plain Language Definition
Dense vectors are long lists of numbers that represent the overall conceptual meaning of a sentence or paragraph, without focusing on specific words. Two sentences can have completely different words but very similar dense vectors if they mean the same thing. This is how AI search understands synonyms, related concepts, and paraphrased queries.
Technical Definition
Continuous low-dimensional vector representations produced by deep neural network encoders that project semantic concepts into a shared embedding space where semantic proximity corresponds to vector distance — enabling meaning-based rather than word-based retrieval.
Why This Matters for AI Search Visibility
Dense vector retrieval is why your content does not need to contain the exact words a user typed. Semantically rich content that covers a topic thoroughly will have dense vectors close to many different question phrasings, expanding the query surface your content can be retrieved for.