Embedding
A numerical representation of text, images, or other data that captures semantic meaning.
An Embedding is a numerical vector (typically hundreds to thousands of dimensions) that represents the semantic meaning of text, images, or other content. Similar content produces similar vectors; embeddings enable semantic search, similarity matching, clustering, and many ML applications.
The embedding for 'happy' and 'joyful' will be very close in vector space, even though they share no characters. The embedding for 'happy' and 'apple' will be far apart.
Related terms
A database optimized for storing and searching high-dimensional vector embeddings.
A technique that combines LLMs with retrieval of external information to ground responses in facts.
A neural network trained on vast text data to understand and generate human language.
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