Multi-modal interfaces are becoming increasingly popular for app developers. These interfaces allow users to interact with apps in a variety of ways by combining different modes of input and output, such as voice, touch, and visuals, to create a more interactive and engaging user experience. In this blog we will overview how you can use ...
In this post, we will show you how to use the Summarize Skill, one of the many skills available in the Semantic Kernel repo, to create concise and actionable summaries of your chat conversations. The Summarize Skill uses AI to extract the main points, topics, and action items from any text input. You can use it to quickly review what was ...
Semantic Kernel (SK) is a lightweight SDK that lets you mix conventional programming languages, like C# and Python, with the latest in Large Language Model (LLM) AI “prompts” with prompt templating, chaining, and planning capabilities. Its Planner Skill allows users to create and execute plans based on semantic queries. Recently, the ...
UPDATE: See the blog post: How to deploy Semantic Kernel to Azure as a web application service on the easiest way to deploy Semantic Kernel to your Azure instance. If you have been following the Semantic Kernel GitHub repo, you have probably experimented with some of the examples and seen how powerful and flexible the platform is for ...
What if you could use natural language to create software? What if you could leverage the power of a large-scale language model that can generate code, data, and text from simple prompts? What if you could balance the trade-offs between leverage and precision, uncertainty and interaction, complexity and simplicity? These are some of the ...
UPDATE: This Sample has been deprecated. See the Chat Copilot example app on how to use embeddings and memories. Have you ever wanted to Ask questions to a GitHub repo? How many files are there, what languages are used, who contributed to it, what topics are covered, and so on? If you are a developer, researcher, or ...
Artificial intelligence (AI) and Large Language Models (LLM) are helping to transform the way we develop and interact with software. From chatbots to code generators, natural language is the future of user interaction, delivering delightful and intelligent "copilot" experiences. As these AI models become more prevalent and accessible, ...
