98. RAG: Give Your AI Access to Your Documents
The article discusses Retrieval Augmented Generation (RAG), a method that enhances AI's ability to provide accurate answers by accessing relevant documents. Unlike traditional fine-tuning, RAG allows for real-time updates and precise citations from a knowledge base. The piece outlines the RAG pipeline and compares it to fine-tuning for different use cases.
- ▪RAG retrieves relevant documents before generating answers, improving accuracy.
- ▪Fine-tuning is best for teaching style and behavior, while RAG is ideal for factual knowledge.
- ▪The RAG pipeline consists of indexing, retrieval, and generation steps.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 1358056) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Akhilesh Posted on May 26 98. RAG: Give Your AI Access to Your Documents #ai #python #beginners #productivity You ask ChatGPT about your company's internal policies. It makes something up. It sounds confident. It's wrong. That's the hallucination problem. LLMs generate text based on what they learned during training. If the answer wasn't in the training data, they fabricate one that sounds plausible. RAG (Retrieval Augmented Generation) fixes this.
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