microsoftJun 1, 2026

Scaling AI for silicon - Engineering@Microsoft (opens in new tab)

The provided Microsoft Engineering blog URL no longer contains the article “Scaling AI for Silicon.” Instead, it returns a 404 error page, so the post’s argument, technical details, and conclusion cannot be determined from the supplied content. ## Missing Article - The requested URL points to `devblogs.microsoft.com/engineering-at-microsoft/scaling-ai-for-silicon/`. - Microsoft reports: “Oops, 404 Error! That page can’t be found.” - No article text, author, publication date, or technical discussion is included. ## Available Resources - Links are provided to Microsoft Docs, Visual Studio, Microsoft Learn, Developer Community, and the Dev Blogs FAQ. - The page also lists Microsoft’s other technology blogs, including Azure, .NET, AI, engineering, and Windows-related blogs. - A link to the Engineering@Microsoft blog homepage is available, but the requested post itself is not. The article cannot be accurately summarized without its original text or an accessible replacement URL.

aiscalabilitysemiconductor-designsilicon-engineering

microsoftMar 3, 2025

How Microsoft Engineers Build AI: Learn about scalable RAG-enabled AI Apps (opens in new tab)

Microsoft’s new *How Microsoft Engineers Build AI* video series explains how its teams develop AI applications at scale. The first episode focuses on retrieval-augmented generation (RAG), using Copilot for Azure’s Ask Learn plugin as a practical example. It shows how RAG can combine proprietary data with large language models to deliver accurate, contextually relevant answers. ## Building AI Applications with RAG - RAG is presented as a practical way to improve AI applications without relying solely on model fine-tuning. - It retrieves relevant information from a knowledge base and provides that context to an LLM when generating responses. - The approach is useful for applications that need current, domain-specific, or proprietary information. ## The Ask Learn Plugin - Microsoft engineers explain how they built the Ask Learn RAG plugin for Copilot for Azure. - The plugin helps Azure developers find answers quickly within their existing workflow. - The project involved product managers and engineering leaders sharing development challenges, design decisions, and best practices. ## Challenges in Developing Reliable RAG - Selecting the right source content is essential for producing useful answers. - Data must be preprocessed effectively before it can be retrieved. - RAG systems require careful performance evaluation to measure accuracy and relevance. - Keeping responses accurate and up to date requires ongoing improvements to content and retrieval methods. ## Broader Microsoft Applications - The episode discusses RAG implementations across: - Copilot in Azure - Microsoft Security Copilot - Dynamics 365 Business Central - These examples demonstrate how RAG can support different products and business scenarios. The episode is intended as a practical introduction for developers building RAG-based applications, covering prototyping, data management, evaluation, and common pitfalls. Developers can explore the series alongside Microsoft Learn resources and Azure AI development tools such as Visual Studio and GitHub Copilot.

aillmmachine-learninggithub-copilot+4