A dense vector representation of text in a high-dimensional space where semantic similarity corresponds to geometric proximity. Used for search, clustering, ...
Turning words into secret number codes so the computer can understand how similar or different things are.
A way of converting text into numbers that capture meaning — similar words get similar numbers, so the AI can understand relationships.
A dense vector representation of text in a high-dimensional space where semantic similarity corresponds to geometric proximity. Used for search, clustering, and recommendation.
A learned mapping from discrete tokens or passages to continuous vectors in ℝⁿ, where cosine similarity approximates semantic relatedness. Fundamental to vector search, RAG retrieval, and representation learning.
A function f: X → ℝⁿ mapping inputs to a metric space where the distance function approximates a target similarity — trained via contrastive loss, producing representations useful for nearest-neighbor retrieval, clustering, and downstream transfer.
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