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🚨 Everyone says "RAG is dead" — but I say: It’s just been badly implemented. I’ve worked on AI systems where Retrieval-Augmented Generation (RAG) either changed the game… or completely flopped. Here’s the hard truth 👇 --- 🤯 Most teams mess up

LLM Capabilities, t2i generation via inference and resonance inside vector DB of the model is what makes images as this possible. Via : Midjourney

I feel pride in announcing our Made in India, Real-Time Vector Database - SwarnDB. SwarnDB is a SarthiAI initiative towards an effort to create an end to end eco-system for the future of AI. We tested SwarnDB with 100K vector records of 1536 dime

🚀 Excited to share my latest YouTube video! demonstrate how to integrate Microsoft's Semantic Kernel with Qdrant, the open-source vector database, to build an intelligent question-answering system for Wikipedia pages citeturn0search3 In this tu

💡 5 Things You Need to Master for learn for integrating AI into your project 1️⃣ Retrieval-Augmented Generation (RAG): Combine search with AI for precise and context-aware outputs. 2️⃣ Vector Databases: Learn how to store and query embeddings for e

Which LLM Model is bettter in terms of performance?

Which one is at the top in terms of Coding ??

Hi everyone. Have anyone used any natural language to SQL query LLm model(open source) which is ready for production usecase. Also is there any hosted solution available for production level like plug and play kind of.