How to Improve LLMs with RAG - Overview and Python Code

Learn about Retrieval Augmented Generation (RAG) and its application in improving large language models in this beginner-friendly video tutorial. Explore the concept of RAG, understand its workings through text embeddings and retrieval, and discover how to create a knowledge base. Follow along with a practical example that demonstrates improving a YouTube comment responder using RAG techniques. Gain insights into the limitations of language models and how RAG addresses them. Access accompanying resources including a series playlist, code examples on GitHub and Google Colab, and a detailed blog post for further learning.

Intro -
Background -
2 Limitations -
What is RAG? -
How RAG works -
Text Embeddings + Retrieval -
Creating Knowledge Base -
Example Code: Improving YouTube Comment Responder with RAG -
What's next? -