Multimodal Retrieval-Augmented Generation (RAG) with Vector Database

Multi-modality elevates the capabilities of neural network models to a whole new level. By leveraging contrastive learning and specialized model architectures, we can create a unified vector space for images and text, enhancing multimodal representations. This talk will share insights into building image-text search and Composite Image Retrieval (CIR) using multimodal embeddings and the Milvus open source vector database, demonstrating how multi-modality unlocks new use cases in Retrieval-Augmented Generation (RAG). ▼ ▽ JOIN THE COMMUNITY - MILVUS Discord channel Join this active community of Milvus users to get help, learn tips and tricks on how to use Milvus, or just get to be part of a vibrant community of smart developers! https://discord.com/invite/8uyFbECzPX ▶ CONNECT WITH US X: https://twitter.com/zilliz_universe LINKEDIN: https://www.linkedin.com/company/zilliz/ WEBSITE: https://zilliz.com/ PODCAST: https://creators.spotify.com/pod/show/chloe-williams8/episodes/Inside-the-AI-Agent-Revolution-e2ug0dh/a-abp1mtd