Neural networks that convert text, images, or other data into dense vector representations. Enable semantic understanding by mapping similar concepts to nearby points in vector space.
Embedding models transform raw data (text, images, audio) into dense numerical vectors that capture semantic meaning, enabling AI applications to understand and compare content.
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