AI | Getting Practical with RAG | Beyond the HYPE! скачать в хорошем качестве

AI | Getting Practical with RAG | Beyond the HYPE!

In this episode, I demonstrate how to build simple yet practical RAG (Retrieval-Augmented Generation) applications using Mistral and Llama 3.2 running locally via Ollama. Source code: https://github.com/vensan7888/AI-Lear... We walk through working with both local and remote knowledge sources, store them in a vector database (FAISS), and enhance the system with persistent storage so knowledge can be reused across sessions. You’ll see the complete RAG workflow in action: "Documents - Chunking - Embeddings - Vector DB (FAISS) - User Query - Embedding - Similarity Search - Relevant Context - LLM - Final Answer" This episode is ideal for developers who want a hands-on, local-first understanding of RAG and how to build grounded, scalable LLM applications without relying entirely on the cloud. Chapters: 00:00 Intro 01:30 Build 'RAG' with Local knowledge 11:00 Build 'RAG' Remote knowledge 15:34 Enhance 'RAG' applications with Persistent data 21:55 Conclusion #CreatorJourney #aicommunity #LLM #TechPodcast #AIPlatforms #AIEducation #AIInsights #AI #PodcastLaunch #ArtificialIntelligence #TechLearning #multimodelAI #ollama #texttoimageAI #imagetotextAI #RAG #Agents