Generative AI

CHAPTER 1AI in a Nutshell

No other field of technology has such inconsistent jargon as artificial intelligence (AI). From mainstream media to tech influencers to research scientists, each layer of media has contributed to that confusion. In order of their degree of contribution and frequency, I observed mainstream media simplifying and misusing terms consistently, tech influencers misunderstanding the tech in-depth, and even some research scientists over-complicating their model findings with fancy terms. By no means do I intend to criticize research scientists. They are the backbone of everything discussed in this book. Their work offers solutions to a plethora of problems, making AI the umbrella term for almost every intelligent problem. However, its interdisciplinary nature, the rapid advancements in this space, and AI's general complexity make it already difficult to gain a clear understanding of this field. I am convinced that consistent and clear language would help to understand this topic area.

We can see two broad classes in AI: generative AI, the subject of this book, and discriminative AI. The latter is the traditional and better-known part of AI. Before delving into both AI classes, let's take a moment to understand the broader picture of AI, machine learning (ML), deep learning (DL), and the process of training models, to avoid getting ahead of ourselves.

What Is AI?

Even though AI includes a broad spectrum of intelligent code, the term is often incorrectly used. ...