In this video, we dive into Retrieval-Augmented Generation (RAG), a powerful method for enhancing AI with access to external data sources. We’ll explore how RAG works, why it’s valuable, and when to use it compared to fine-tuning models. You’ll gain a clear understanding of RAG’s benefits, how it complements large language models, and when it’s best to use both RAG and fine-tuning for robust AI solutions. Perfect for AI enthusiasts, tech professionals, or anyone curious about advanced AI applications!

Key Points Covered:

• What is Retrieval-Augmented Generation (RAG)?

• How RAG systems work with external data

• The differences between RAG and fine-tuning

• Examples of RAG applications in business and AI workflows

• When to combine RAG with fine-tuning for the best results

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