Ready to build AI-powered apps? Discover how .NET developers can create powerful generative AI solutions using C#, ML.NET, and Semantic Kernel. Learn to leverage existing skills to build enterprise-grade chatbots, content generators, and more - Python not required.

I explored Google Gemini and was impressed by its speed compared to ChatGPT! My hands-on experience, from coding .NET regex to using the free API tier in Google AI Studio, is detailed in this article. Even though Gemini's Semantic Kernel integration is new, I easily adapted an OpenAI example. If you're curious about a powerful OpenAI alternative, especially within the Google ecosystem, you need to read this.

Recently, I explored using Semantic Kernel and OpenAI for more accurate page scanning. By converting HTML to markdown and extracting metatags with XPath, I reduced input size and improved efficiency. OpenAI’s new JSON output feature further allowed me to receive structured data, making the process more reliable.

I was recently working on learning more about using Dataframes and Polyglot Notebooks with C# and needed some sample data to work with. At first I started by looking for some examples online, but I wanted to write a blog about my experience and wanted my own sample of data.