We process the world through all of our senses, not just text. Your AI shouldn't be stuck with just one. Humans don't process information in just one format – we digest information with photos, graphs, charts, and more to understand the world. Why should our AI systems be limited to text-only retrieval? Enter ๐ ๐๐น๐๐ถ๐บ๐ผ๐ฑ๐ฎ๐น ๐ฅ๐๐ – retrieval augmented generation that works across multiple modalities like images and text. In this new Free @DataCamp course with @_jphwang, youโll learn exactly how to go from simple LLM calls to multi-modal RAG workflows with Weaviate. Sign up here: datacamp.com/courses/end-to-โฆ ๐ฆ๐ผ, ๐ต๐ผ๐ ๐ฑ๐ผ๐ฒ๐ ๐บ๐๐น๐๐ถ๐บ๐ผ๐ฑ๐ฎ๐น ๐ฅ๐๐ ๐๐ผ๐ฟ๐ธ? ๐ ๐๐น๐๐ถ๐บ๐ผ๐ฑ๐ฎ๐น ๐๐บ๐ฏ๐ฒ๐ฑ๐ฑ๐ถ๐ป๐ด ๐ ๐ผ๐ฑ๐ฒ๐น๐ These models understand multiple data types in a ๐ซ๐ฐ๐ช๐ฏ๐ต ๐ฆ๐ฎ๐ฃ๐ฆ๐ฅ๐ฅ๐ช๐ฏ๐จ ๐ด๐ฑ๐ข๐ค๐ฆ – meaning similar concepts cluster together regardless of whether they're images, text, audio, or video. ๐๐ป๐-๐๐ผ-๐๐ป๐ ๐ฆ๐ฒ๐ฎ๐ฟ๐ฐ๐ต Once modalities share an embedding space, you can search across them: โข Use text queries to find relevant images โข Search with audio to retrieve matching video clips โข Find text descriptions from image inputs This is ๐ฐ๐ฟ๐ผ๐๐-๐บ๐ผ๐ฑ๐ฎ๐น ๐ฟ๐ฒ๐ฎ๐๐ผ๐ป๐ถ๐ป๐ด in action – understanding relationships and context across different data types, just like humans do naturally. ๐ ๐๐น๐๐ถ๐บ๐ผ๐ฑ๐ฎ๐น ๐ฅ๐๐ ๐ถ๐ป ๐ฃ๐ฟ๐ฎ๐ฐ๐๐ถ๐ฐ๐ฒ Instead of just retrieving text documents, multimodal RAG retrieves relevant images, diagrams, charts, or videos to augment LLM responses. This enables: โข Visual question answering systems โข Richer context for generation โข More comprehensive and accurate outputs ๐ง๐ฟ๐ฎ๐ฑ๐ฒ-๐ผ๐ณ๐ณ๐ ๐๐ผ ๐ฐ๐ผ๐ป๐๐ถ๐ฑ๐ฒ๐ฟ: โข Requires aligned multimodal datasets (challenging to collect) โข More complex model architectures than single-modality systems โข Higher computational costs for training and inference ๐๐ฒ๐๐๐ถ๐ป๐ด ๐๐๐ฎ๐ฟ๐๐ฒ๐ฑ ๐๐ถ๐๐ต ๐ช๐ฒ๐ฎ๐๐ถ๐ฎ๐๐ฒ: Weaviate already integrates with multimodal embedding models from Cohere, Google, NVIDIA, Hugging Face, and more. This allows you to use embeddings in a joint space, enabling nearVector and nearImage searches across both modalities. Download this free Advanced RAG guide for the full picture: weaviate.io/ebooks/advanced-โฆ
โ View original post on X โ @marcusborba, 2025-10-30 11:00 UTC
