␡
- 1.1 Introduction
- 1.2 Chapter contents
- 1.3 Communication and neuro linguistic programming (nlp)
- 1.4 Abstraction
- 1.5 Finding the right level of abstraction for Generative AI
- 1.6 Choice of Generative AI
- 1.7 Applying Generative AI to an example problem domain
- 1.8 Modeling in Generative Analysis
- 1.9 Chapter summary
This chapter is from the book
This chapter is from the book
This chapter is from the book
This chapter is from the book
1.6 Choice of Generative AI
Our choice of a specific Generative AI for this example is somewhat arbitrary. We have tested Google Gemini, ChatGPT, and Microsoft Copilot, and we decided to use Copilot because it is readily available via the Microsoft Edge browser and is easy to use. When we show Generative AI examples in this book, we will adopt the standard template shown in Figure 1-2.
Figure 1-2 Template for conversations
We will omit Suggested prompts if they are not interesting, and for brevity we will only include Learn more if it adds anything to the Response.
In the next section, we will consider a simple problem domain to find the right level of abstraction for Generative AI prompts to generate code and UML models.
