Build Better Multimodal RAG Pipelines with FiftyOne, LlamaIndex, and Milvus

Multimodal Large Language Models like GPT-4V, Gemini Pro Vision and LLaVA are ushering in a new era of interactive applications. The addition of visual data into retrieval augmented generation (RAG) pipelines introduces new axes of complexity, reiterating the importance of evaluation. In this webinar, you'll learn how to compare and evaluate multimodal retrieval techniques so that you can build a highly performant multimodal RAG pipeline with your data. The data-centric application we will be using is entirely free and open source, leveraging FiftyOne for data management and visualization, Milvus as a vector store, and LlamaIndex for LLM orchestration.

Topics covered:
Applications of multimodal RAG
The challenges of working with multiple multimodality
Advanced techniques for multimodal RAG
Evaluating multimodal retrieval techniques

Resources:
LLM Visualization: https://bbycroft.net/llm
FifyOne Multimodal RAG plugin: https://github.com/jacobmarks/fiftyon...
FifyOne image captioning plugin: https://github.com/jacobmarks/fiftyon...
Voxel51 documentation: https://docs.voxel51.com/
FiftyOne and Milvus: https://docs.voxel51.com/integrations...


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