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Building AI Applications with Microsoft Semantic Kernel

Building AI Applications with Microsoft Semantic Kernel

By : Lucas A. Meyer
3.9 (9)
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Building AI Applications with Microsoft Semantic Kernel

Building AI Applications with Microsoft Semantic Kernel

3.9 (9)
By: Lucas A. Meyer

Overview of this book

In the fast-paced world of AI, developers are constantly seeking efficient ways to integrate AI capabilities into their apps. Microsoft Semantic Kernel simplifies this process by using the GenAI features from Microsoft and OpenAI. Written by Lucas A. Meyer, a Principal Research Scientist in Microsoft’s AI for Good Lab, this book helps you get hands on with Semantic Kernel. It begins by introducing you to different generative AI services such as GPT-3.5 and GPT-4, demonstrating their integration with Semantic Kernel. You’ll then learn to craft prompt templates for reuse across various AI services and variables. Next, you’ll learn how to add functionality to Semantic Kernel by creating your own plugins. The second part of the book shows you how to combine multiple plugins to execute complex actions, and how to let Semantic Kernel use its own AI to solve complex problems by calling plugins, including the ones made by you. The book concludes by teaching you how to use vector databases to expand the memory of your AI services and how to help AI remember the context of earlier requests. You’ll also be guided through several real-world examples of applications, such as RAG and custom GPT agents. By the end of this book, you'll have gained the knowledge you need to start using Semantic Kernel to add AI capabilities to your applications.
Table of Contents (14 chapters)
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Free Chapter
1
Part 1:Introduction to Generative AI and Microsoft Semantic Kernel
4
Part 2: Creating AI Applications with Semantic Kernel
9
Part 3: Real-World Use Cases
11
Chapter 8: Real-World Use Case – Making Your Application Available on ChatGPT

Generative AI and how to use it

Generative AI refers to a subset of artificial intelligence programs that are capable of creating content that is similar to what humans can produce. These systems use training from very large datasets to learn their patterns, styles, and structures. Then, they can generate entirely new content, such as synthesized images, music, and text.

Using GenAI as consumer or end-user is very easy, and as a technical person, you probably have already done it. There are many consumer-facing AI products. The most famous is OpenAI’s ChatGPT, but there are many others that have hundreds of millions of users every day, such as Microsoft Copilot, Google Gemini (formerly Bard), and Midjourney. As of October 2023, Meta, the parent company of Facebook, WhatsApp, and Instagram, is making GenAI services available to all its users, increasing the number of GenAI daily users to billions.

While the concept of GenAI has existed for a while, it gained a lot of users...

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