From the course: AWS Certified Generative AI Developer - Professional (AIP-C01) Cert Prep

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Vector databases, embeddings, and RAG explained

Vector databases, embeddings, and RAG explained

From the course: AWS Certified Generative AI Developer - Professional (AIP-C01) Cert Prep

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Vector databases, embeddings, and RAG explained

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You ask ChatGPT a question about your company's internal documents and it has no idea what you're talking about. You try to search your database for documents about customer complaints, but all you get back are exact keyword matches that miss half of what you actually need. Here's the problem. Traditional databases don't understand meaning. They only match exact words. But what if your database could actually understand concepts, context, and similarity? I'm going to show you the technology that's powering the next generation of AI applications – vector databases, embeddings, and reg. And by the end of this video, you'll understand exactly how companies like ChatGPT, NotionAI, and thousands of others are building smarter search systems. So first things first. What exactly are we talking about here? Let me break down these three concepts because they work together like a well-oiled machine. Embeddings are basically numerical representations of text, images, or any data that capture…

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