From the course: Securing Generative AI: Strategies, Methodologies, Tools, and Best Practices
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Securing vector databases
From the course: Securing Generative AI: Strategies, Methodologies, Tools, and Best Practices
Securing vector databases
- [Instructor] Let's go over how to secure vector databases. By now, you know that vector databases are specialized database systems that are designed to efficiently manage and query high dimensional vector data. They're integral to recommendation systems, to image and video search, natural language processing, and many other applications including retrieval-augmented generation. And as a matter of fact, as you see on the screen, you can use a retrieval-augmented generation system, as you learned earlier, to retrieve relevant data from that vector database and then provide additional context to an AI model. So these vector databases are essential for applications that rely on embeddings. And most vector databases can handle very large data sets with millions or billions of vectors. They enable similarity search, for example, nearest neighbor searches, as well as clustering and classification of data. But again, vector databases are a key component of retrieval-augmented generation…
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