Summary
Generative AI is a rather rapidly growing area, having huge disruptive potential for industries and changing areas of our lives. In contrast, applications of generative AI include very realistic image generation and generation of text, accelerated drug discovery, and enriched creative expression.
One of the key points regarding this is an understanding of the different generative models, such as VAEs, GANs, and autoregressive models, that provide insight into how technologies work and where they can be applied. It would also, however, be important to state the many problems and limitations generative AI faces, including data quality, computational resources, ethical considerations, and even creativity.
In the next chapter, we will learn about the principles of agentic systems, which include the concepts of agency and autonomy, the characteristics of intelligent agents, various architectures of intelligent systems, and multi-agent systems.
