Multimodal Embeddings and RAG: Gemini Embedding 2 & Weaviate

AI Impact Summary

The blog post details a practical guide to multimodal embeddings and Retrieval-Augmented Generation (RAG) using tools like Weaviate and Gemini, highlighting the shift towards natively multimodal models. A key takeaway is the 'contrastive learning' approach used to align embeddings across text, images, audio, and video, addressing the limitations of traditional text-only embeddings. The discussion emphasizes design decisions like native vs. bridge-based embeddings and chunking strategies, which significantly impact retrieval accuracy.