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Every day you skip reading this book = a missed opportunity. AI Engineering by @chipro is gold: • Build with LLMs • RAG & agents • Dataset engineering • Evaluation metrics that matter This isn’t just theory. It’s how to build. #AI #LLM #RAG #Tec

Learn how to build a RAG application (!) using @eyelevelai with its super solid ETL pipeline for performing RAG on complex docs (!!) using @GroqInc for fast AI inference (!!!) and expose your local @FastAPI server over the internet via @ngrokHQ h

Retrieval-Augmented Generation (RAG) is a GenAI framework that enhances large language models (LLMs) by incorporating information from external knowledge bases, improving accuracy, relevance, and reliability of generated responses. Here's a more det

I am thinking about an AI model with multiple languages support especially devnagari script languages , we are planning to build an RAG to parse a document and provide the data to the LLM , is this idea feasible and useful suggestions are welcomed

If I were learning RAG from scratch in 2025... here's exactly how I'd do it. But here I bring you the ultimate resource list for absolutely no cost. RAG is one of the most practical, production-ready LLM patterns today. Here's All you need to get s

How RAG Gen AI Helps Businesses Retrieval-Augmented Generation (RAG) enhances AI by combining real-time data retrieval with generative models, making it highly effective for businesses. Key Benefits: Better Decision-Making – Provides real-time ins

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

With AI and LLM do you think we can build a better AI based smartphone ?

Working on a cool AI project, that involves vector db and LLM fine-tuning

If anyone interested to work on a quick python project Gen AI RAG for learning purpose, please reply. Skills : Python Flask and SQL.