Abstract
<jats:p>Generative AI represents a significant advancement in machine learning, distinguishing itself from traditional AI by its ability to create new and original content such as text, images, and code. This chapter provides a comprehensive overview of Generative AI, covering its core models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based architectures such as GPT and DALL·E. It explores diverse applications across various sectors, including art, education, and science. Furthermore, the chapter delves into the critical societal implications of this technology, addressing issues like intellectual property, misinformation, and artistic authenticity. By examining both the technical underpinnings and the ethical landscape, this work aims to foster a human-centered and responsible approach to developing and using generative systems.</jats:p>