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Fine-Tuning vs. RAG Explained in 4 Minutes | AI for Beginners

What’s the difference between fine-tuning and retrieval-augmented generation (RAG) when it comes to large language models (LLMs)? In this quick breakdown, we’ll explain how fine-tuning and RAG work, highlight their key differences, and show when it makes sense to use one over the other—or even combine both for maximum performance. 🌟***OTHER VIDEOS YOU MIGHT ENJOY***🌟 • Build your own chatbot (using RAG) with Amazon Bedrock and Lex:    • AWS Project: Build an AI-Powered Chatbot w...   • Getting started with Amazon Bedrock:    • Amazon Bedrock Tutorial – Model Access, Pl...   🌟***MY AWS COURSES***🌟 If you’re interested in getting AWS certifications, check out these full courses. They include lots of hands-on demos, quizzes and full practice exams. Use FRIENDS10 for a 10% discount! AWS Certified Cloud Practitioner: https://academy.zerotomastery.io/a/af... AWS Certified Solutions Architect Associate: https://academy.zerotomastery.io/a/af... 🌟***TIMESTAMPS***🌟 00:00 – What’s the difference between fine-tuning and RAG when it comes to LLMs? 00:41 – How does fine-tuning work with an LLM? 01:47 - How does retrieval-augmented generation (RAG) work with an LLM? 02:56 – A side-by-side comparison chart of fine-tuning vs. RAG 03:25 – Using both fine-tuning and RAG together