Multimodal RAG: A Beginner-friendly Guide (with Python Code)

🤝 Want your team maximizing Claude? I run 1:1 and team AI workshops for companies doing $1M+ per year: https://aibuilder.academy/yt/Y7pNmocrmi8 Multimodal RAG improves an AI model's responses by providing relevant information stored in text and non-text formats. Here, I discuss 3 ways to build an MRAG system and share an example implementation with Python. Resources: 📰 Blog: https://medium.com/towards-data-science/multimodal-rag-process-any-file-type-with-ai-e6921342c903?sk=dabb0a46b1c53c3072f8f61772afa554 💻 GitHub Repo: https://github.com/ShawhinT/YouTube-Blog/tree/main/multimodal-ai References: [1] RAG: https://youtu.be/Ylz779Op9Pw [2] Multimodal LLMs: https://youtu.be/Ot2c5MKN_-w [3] Multimodal Embeddings: https://youtu.be/YOvxh_ma5qE Introduction - 0:00 What is RAG? - 1:12 Multimodal RAG (MRAG) - 4:01 3 Levels of MRAG - 5:26 Example code: Multimodal Blog QA Assistant - 10:52 Demo (Gradio) - 24:44 Limitations - 25:28