What Are Embeddings? (RAG Module)
Introduction to Embeddings
Let’s continue from where we left off.
In the last lesson, we learned that AI models need retrieval to give accurate answers.
But that raises a big question.
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Summary – Key Takeaways
Let’s recap in simple terms.
Embeddings convert text into numerical representations.
Texts with similar meaning end up close to each other.
This allows systems to search based on meaning, not exact words.
That’s how AI systems find the right information during retrieval.
And that’s why embeddings are the backbone of modern RAG systems.
Citations :
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