Showing results for AI - Developer Support

David Minkovski explores using Azure OpenAI and Rust to Build Intelligent and Scalable AI Systems Motivation For the past few months, I’ve had the pleasure of taking the front seat to some really fascinating and exciting AI projects, thanks to my amazing customers and colleagues at Microsoft. During these sessions, I noticed a common chall...

AJ Enns reflects on his journey as a new developer and the impact of AI as an integrated, coding assistant for improving developer velocity. The year is 2024, and AI has been around for a while. ChatGPT broke onto the scene and changed the world forever. As soon as I heard about it, the first thing I did was try to learn Blazor with the help...

Linkai Yu explores the retrieval-augemented generation pattern with Azure OpenAI Assistants API. The Retrieval-Augmented Generation (RAG) pattern is the standard for integrating ground AI with local data. One powerful way to implement RAG is through the function call or tool call feature in the Function Call API. When examining the samples p...

Monu Bambroo explores Whisper, a speech to text model from OpenAI that you can use to transcribe audio files. The model is trained on a large dataset of English audio and text. The model is optimized for transcribing audio files that contain speech in English. The model can also be used to transcribe audio files that contain speech in other languag...

Tahir Naveed walks through how to measure prompt response times with Microsoft Copilot Studio and explores considerations that factor into the overall performance of these requests. Building custom copilots (GenAI chatbots) in Microsoft Copilot Studio is amazing. Especially with the new functionalities which were released in Microsoft Build ...

Jordan Bean explores how to visualize Semantic Kernel & Azure OpenAI plans using Mermaid. Using the function calling ability of Semantic Kernel/OpenAI is very exciting from an application development point of view. Instead of hard-coding paths though the system, Semantic Kernel & OpenAI can decide for themselves what plugins to call,...

In this multi-part series, Jordan Bean shares how to enhance a chatbot to retrieve data from multiple data sources and orchestrate plans with C# Semantic Kernel, planner, and Azure Open AI. In the previous post, I detailed how the demo app runs. In this post, let’s talk about some of the techniques & technologies I used to make the demo ...

In this multi-part series, Jordan Bean shares how to enhance a chatbot to retrieve data from multiple data sources and orchestrate plans with C# Semantic Kernel, planner, and Azure Open AI. In the previous post, we talked about the implementation details of how the demo app works & how to set up Semantic Kernel, with the  and Azure OpenA...

In this multi-part series, Jordan Bean shares how to enhance a chatbot to retrieve data from multiple data sources and orchestrate plans with C# Semantic Kernel, planner, and Azure Open AI. In the previous post, we discussed how the RAG pattern isn’t enough to answer complex user questions. We talked about using Semantic Kernel to orchestrat...

In this multi-part series, Jordan Bean shares how to enhance a chatbot to retrieve data from multiple data sources and orchestrate plans with C# Semantic Kernel, planner, and Azure Open AI. As discussed in the previous post about Azure OpenAI, using the Retrieval Augmented Generation (RAG) pattern is a simple & effective way to enable Az...