Learn Retrieval Augmented Generation (RAG) in under 10 minutes

Retrieval-augmented generation (RAG) is a technique for enhancing the accuracy and reliability of generative AI models with facts fetched from external sources.

In other words, it fills a gap in how LLMs work. Under the hood, LLMs are neural networks, typically measured by how many parameters they contain. An LLM’s parameters essentially represent the general patterns of how humans use words to form sentences.

here is a short introductory course on learning the fundamentals of RAG which is an important topic to grasp in the world of Generative AI. Enjoy!

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