#vectors

机器辅助翻译草稿 (Chinese) for "Embeddings": Dense numerical vector representations of words, sentences, or other data that capture semantic meaning. Similar concepts have similar embeddings (nearby in vector space), allowing AI systems to measure meaning similarity mathematically rather than relying on exact keyword matches.

“示例草稿: The search engine uses embeddings to find relevant results even when the query words don't appear in the document.”

机器辅助翻译草稿 (Chinese) for "Vector Database": A specialized database optimized for storing and querying high-dimensional vector embeddings. Vector databases power semantic search, recommendation systems, and RAG architectures by efficiently finding the most similar vectors to a given query.

“示例草稿: We stored all our documentation as embeddings in a vector database so the AI could find relevant passages instantly.”