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Mastering Microsoft Dynamics 365 Business Central

Mastering Microsoft Dynamics 365 Business Central

By : Stefano Demiliani, Tacconi
4.9 (17)
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Mastering Microsoft Dynamics 365 Business Central

Mastering Microsoft Dynamics 365 Business Central

4.9 (17)
By: Stefano Demiliani, Tacconi

Overview of this book

This book dives straight into guiding you through the process of building real-world solutions with the AL language and Visual Studio Code. It emphasizes best practices and extensibility patterns to ensure your extensions are well-structured, maintainable, and meet the needs of modern businesses. You'll learn advanced AL techniques, report creation methods, debugging strategies, and how to leverage telemetries for monitoring. Additionally, it covers performance optimization practices and API integration to help you create efficient and interconnected solutions. With a focus on extension development, this new edition allows you to jump right into coding without spending time on setup processes. This book introduces new chapters covering essential tasks that Business Central developers frequently encounter, such as file handling and printing management. Finally, the book expands its scope by including chapters on various integration aspects, including VS Code extensions, GitHub DevOps, Azure services, and Power Platform integrations. We’ll wrap up by covering Copilot capabilities in Business Central and how you can create your own generative AI copilots. By mastering these concepts and techniques, you'll be well-equipped to create powerful and customized solutions that extend the capabilities of Dynamics 365 Business Central.
Table of Contents (21 chapters)
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19
Other Books You May Enjoy
20
Index

Introduction to generative AI main concepts

The success of ChatGPT, developed by OpenAI, has generated a worldwide rise in interest in generative AI. As we can see from the following Google Trends data, interest in generative AI increased significantly after ChatGPT was released in November 2022:

Figure 18.1: Google Trends data for ChatGPT

Let’s take a glance at a high-level overview of what concepts and terminologies are important to learn in this topic. Firstly, generative AI is a form of artificial intelligence in which models are trained to generate new content based on natural language input. The inputs and outputs of these models can include text, images, audio, and other types of data.

Generative AI models use neural networks to identify the patterns and structures within existing data to generate new and original content.

Generative AI applications are powered by Large Language Models (LLMs, like OpenAI’s GPT-3.5 and GPT-4. Google’...

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