A technical guide on using Azure AI Language Studio to summarize and optimize grounding documents for improving RAG-based AI solutions.
A simple explanation of Retrieval-Augmented Generation (RAG), covering its core components: LLMs, context, and vector databases.
A summary of a keynote talk on essential building blocks for production LLM systems, covering evaluations, RAG, and guardrails.
A technical overview of Obsidian-Copilot, a prototype AI assistant for drafting and reflecting within the Obsidian note-taking app using retrieval-augmented generation.
Explains Retrieval Augmented Generation (RAG) for using ChatGPT with custom data, including a C# implementation sample.
Explains how retrieval-augmented language models like RETRO achieve GPT-3 performance with far fewer parameters by querying external knowledge.
