Daily Learning Post: What Is Generative AI?
Generative AI is a type of artificial intelligence that can create new content—like text, images, music, or even code—by learning patterns from large amounts of data. Imagine tools that write emails for you, generate computer code, or design pictures based on a few instructions; these are powered by generative AI. Example in Everyday Life: Microsoft Copilot (an AI assistant built into products like Word, Excel, and Teams) uses generative AI to help you draft documents, summarize meetings, and answer questions automatically. Why does this matter? Generative AI can save time, spark creativity, and make complex tasks easier for everyone—no coding skills required! Questions for You: What’s one thing you wish an AI tool could do for you? Are you curious to see how Copilot could help in your work or studies? 🗂️ Flashcards: Generative AI Basics Q1: What is Generative AI? A1: Generative AI is a type of artificial intelligence that can create new content—such as text, images, music, or code—by learning from large datasets. Q2: Name one Microsoft tool that uses Generative AI. A2: Microsoft Copilot uses generative AI to help users draft documents, summarize meetings, and answer questions automatically. Q3: Why is Generative AI important? A3: It helps save time, inspires creativity, and makes complex tasks easier—without needing coding skills. Q4: Give an example of a simple task Generative AI can do for you. A4: It can write an email, summarize notes, or suggest creative ideas. For more flashcards and quizzes, visit our Resources section! Comment below or ask anything you want to learn about Generative AI and Copilot!New Member Welcome: Your Hub for Generative AI & Copilot Insights
🎉 Welcome to Generative AI & Copilot Innovators! 🎉 We’re excited to have you join this hub for Microsoft Copilot, AI, and innovation enthusiasts! Purpose: This group connects passionate individuals to share ideas, learn from each other, and accelerate innovation with Generative AI and Microsoft Copilot. Key Topics: Latest Copilot features, tips, and updates Real-world AI use cases and success stories Discussions on generative AI trends and research Resources, tutorials, and community events How to Participate: Introduce yourself in the comments below—share your background and interests! Post your questions, insights, or experiences with Copilot and AI. Join group discussions and respond to others. Share useful resources, news, or opportunities. Suggest topics or events you’d like to see. Let’s collaborate, inspire, and shape the future of AI together!The Future of AI: The paradigm shifts in Generative AI Operations
Dive into the transformative world of Generative AI Operations (GenAIOps) with Microsoft Azure. Discover how businesses are overcoming the challenges of deploying and scaling generative AI applications. Learn about the innovative tools and services Azure AI offers, and how they empower developers to create high-quality, scalable AI solutions. Explore the paradigm shift from MLOps to GenAIOps and see how continuous improvement practices ensure your AI applications remain cutting-edge. Join us on this journey to harness the full potential of generative AI and drive operational excellence.The Future of AI: Maximize your fine-tuned model performance with the new Azure AI Evaluation SDK
In this article, we will explore how to effectively evaluate fine-tuned AI models using the new Azure AI Evaluation SDK. This comprehensive guide is the fourth part of our series on making large language model distillation easier. We delve into the importance of model evaluation, outline a systematic process for assessing the performance of a distilled student model against a baseline model, and demonstrate the use of advanced metrics provided by Azure's SDK. Join us as we navigate the intricacies of AI evaluation and provide insights for continuous model improvement and operational efficiency.The Future of AI Is: Model Choice - From Structured Process To Seamless Platform
Language models are at the heart of generative AI applications. But in just over a year, we've moved from a handful of model providers to 1M+ community variants and more, resulting in the paradox of choice that ends in decision fatigue. In this blog post, we'll look at how developers can rethink their model selection strategy with a structured decision-making process, and a seamless development platform, to help them. This post is part of the Future of AI series jumpstarted by Marco Casalaina with his post on Exploring Multi-Agent AI Systems.
