Problem Zeroth, Tech... • 8m
Most people think of RAG (Retrieval-Augmented Generation) as a text-only thing. But when we apply it to images, it unlocks serious potential — especially in safety, retail, and surveillance. I recently explored Vision-RAG using Weaviate + LangChain to enable text-to-image retrieval from large camera datasets. Here’s a simplified breakdown: 🧠 Query: “Show me all images with a broken bumper” 🔍 Weaviate retrieves semantically matched images (via CLIP embeddings) 🖼️ GenAI or Vision models add context, summaries, or auto-tags 💡 Outcome: Faster QA, visual analytics, or even chatbot interfaces for cameras It’s like giving memory and understanding to your visual data. Would love to hear how others are using RAG outside of just documents.
AI agent developer |... • 17d
🚀 I Built a Fully Local Multimodal RAG System — Here’s Why As an engineering student, I noticed something: we build AI tools using cloud APIs, but in reality, most valuable data is private — legal contracts, medical records, financial audits, insur
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| Technologist | ML ... • 1y
In the ever-evolving AI landscape, a new player is making waves — Deepseek. While OpenAI, Google DeepMind, and Meta AI have been dominant forces, Deepseek is emerging as a formidable contender in the AI race.The recent buzz around Deepseek stems from
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