If you’re not yet familiar with the open-source pgvector extension for PostgreSQL, now’s the time to do so. The tool is extremely helpful for searching text data fast, without needing a specialized database to store embeddings.

Embeddings represent word similarity and are stored as vectors (a list of numbers). For example, the words “tree” and “bush” are related more closely than “tree” and “automobile.” The open-source pgvector tool makes it possible to search for closely related vectors and find text with the same semantic meaning. This is a major advance for text-based data, and an especially valuable tool for building Large Language Models (LLMs)… and who isn’t right now?

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