Embedding
An embedding is a list of numbers that represents the meaning of text (or other data) in a form machines can compare and search.
In Simple Terms
Think of it as a barcode for meaning: different phrases with the same idea get similar codes.
Detailed Explanation
Embeddings turn words, sentences, or documents into fixed-length vectors. Similar meaning produces similar vectors, so you can search by meaning (semantic search) instead of exact keywords. When to use embeddings: for search, recommendations, clustering, and as input to RAG. Common mistakes: mixing embedding models between indexing and querying, or assuming all models use the same scale for similarity.
Related Terms
Artificial Intelligence
The simulation of human intelligence processes by machines, especially computer systems.
Read moreTransfer Learning
Transfer learning is the practice of taking a model already trained on one task or dataset and reusing or adapting it for another. It speeds development and often improves performance when data for the new task is limited.
Read moreMachine Learning
A subset of AI that enables systems to learn and improve from experience without being explicitly programmed.
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