Image created with OpenAI gpt-image-1. Image prompt: Single-panel cartoon with loose, hand‑inked lines, bean‑bodied figures, muted flat colors, minimal props, and deadpan humor: Clothesline hung with socks labeled ‘facts’; sewing‑machine robot stitches them into a patchwork quilt documentation. Large bold title text centered at top: “RAG” Muted colors, flat shading, black ink outlines. 16:9. Caption: “Patches holes in its own memory.”
Introducing Embed 4: Multimodal search for business https://cohere.com/blog/embed-4
“Adversarial patches fool computer vision systems, and retraining models for defense is impractical. This paper introduces a training-free Visual RAG (VRAG) framework using Vision-Language Models (VLMs) to detect these patches by retrieving similar known attacks from a database. https://x.com/rohanpaul_ai/status/1914942566828589225
“Cohere released Embed 4, a SOTA multimodal embedding model to add frontier search and retrieval capabilities to AI apps —128K-token context window —Supports 100+ languages —Optimized for data from regulated industries —Up to 83% savings on storage costs https://x.com/rowancheung/status/1912744190947057969
“I’m excited to release a post which outlines a reference architecture for building agents over your documents 🤖📑 (we call it Agentic Document Workflows) A lot of knowledge work is dominated by PDFs, PowerPoints, Excel. “Basic RAG over your docs” doesn’t capture the full https://x.com/jerryjliu0/status/1915109277498585569
“Vector search with large databases slows down RAG pipelines. Moving the entire search to the GPU hurts LLM performance by using up critical memory. VectorLiteRAG solves this by adaptively partitioning the vector index, placing only frequently accessed “hot” clusters onto the https://x.com/rohanpaul_ai/status/1913951536926834740
“8/ Cohere’s latest Command A and Embed v4 are now available in the Azure AI Foundry model catalog. From intelligent document Q&A to enterprise copilots and scalable search apps, these models are production-ready and developer-friendly. https://x.com/AtomSilverman/status/1913372925807481262
“I’m excited to share @Cohere’s newest model, Embed 4! Embed 4 is the optimal search engine for secure enterprise AI assistants and agents. https://x.com/aidangomez/status/1912129355041358314
“11/ @aidangomez shared @Cohere’s newest model, Embed 4! Embed 4 is the optimal search engine for secure enterprise AI assistants and agents. https://x.com/AtomSilverman/status/1913372932220571661
“🎉 Cohere’s latest Command A and Embed v4 are now available in the Azure AI Foundry model catalog. From intelligent document Q&A to enterprise copilots and scalable search apps, these models are production-ready and developer-friendly. Explore now: https://x.com/Azure/status/1912249571192742139
cohere on X: “Introducing Embed 4: our latest state-of-the-art multimodal embedding model that enables enterprises to securely add powerful search and retrieval capabilities to their agentic AI applications! https://t.co/eTpgA22P7k” / X
https://x.com/cohere/status/1912128813104078999
“11 new types of RAG ▪️ InstructRAG ▪️ Collaborative RAG (CoRAG) ▪️ ReaRAG ▪️ MCTS-RAG ▪️ Typed-RAG ▪️ MADAM-RAG ▪️ HM-RAG ▪️ CDF-RAG ▪️ NodeRAG ▪️ HeteRAG ▪️ Hyper-RAG Save the list and check this out for the links and more info: https://x.com/TheTuringPost/status/1913915061388849613
