🤝 Your team not maximizing Claude? I run 1:1 and team AI workshops for companies doing $10M+ 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
Choose to Build with AI
Matched to Multimodal LLM
AI Maker Residence 3
The third AI workshop taught by our legendary teacher, Nick Sarafa. This is a full-day hands-on training workshop for purposeful co-creation with AI using Claude Code.
Imagine having access to hundreds of billions of dollars of computing power and knowing exactly how to make it work for you through the power of super intelligence.
◆ Fri 09 Oct 2026◆ KOKO Cafe, London◆ With Nick Sarafa
