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 moreMachine Learning
A subset of AI that enables systems to learn and improve from experience without being explicitly programmed.
Read moreBias in AI
Bias in AI is systematic error or unfairness in how a model treats individuals or groups, often reflecting skewed data or flawed design. It can worsen existing inequalities if left unchecked.
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