Introduction to Generative AI Patterns
This chapter provides an overview of key concepts, techniques, and integration patterns related to generative AI that will empower you to harness these capabilities in real-world applications.
We will provide an overview of generative AI architectures, such as transformers and diffusion models, which are the basis for these generative models to produce text, images, audio, and more. You’ll get a brief introduction to specialized training techniques, like pre-training and prompt engineering, that upgrade basic language models into creative powerhouses.
Understanding the relentless pace of innovation in this space is critical due to new models and ethical considerations emerging constantly. We’ll introduce strategies for experimenting rapidly while ensuring responsible, transparent development.
The chapter also introduces common integration patterns for connecting generative AI into practical workflows. Whether crafting chatbots that leverage models in real time or performing batch enrichment of data, we will introduce prototyping blueprints to jumpstart building AI-powered systems.
By the end, you will have a one-thousand-foot view of which generative AI models are available, why experimentation is important, and how these integration patterns can help create value for your organization leveraging generative AI.
In a nutshell, the following main topics will be covered:
- Interacting with AI
- Predictive AI vs generative AI use case ideation
- A change in the paradigm
- General generative AI concepts
- Introduction to generative AI integration patterns
