Building with Gemini Embedding 2: Agentic multimodal RAG and beyond- Google Developers Blog

This post introduces Gemini Embedding 2, a multimodal embedding model that maps text, images, video, audio, and documents into a single embedding space. It details its application in agentic multimodal RAG using task prefixes for optimized embeddings, multimodal search with specific prefixes, search reranking via similarity metrics, and clustering, classification, and anomaly detection using symmetric task prefixes. The post also highlights efficient storage options with Matryoshka Representation Learning (MRL) and cost-saving batch processing.