Advancements and Applications of Generative Artificial Intelligence

Abstract

As a transformative technology, generative artificial intelligence (AI) has emerged in a variety of fields such as image synthesis, text generation, music composition and creative design with diverse applications. The purpose of this paper is to provide a comprehensive overview of recent advances in generative AI techniques. To begin with, we examine the evolution of generative models from traditional methods to state-of-the-art deep learning approaches like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers. During the following part of the paper, we discuss generative AI and its wide-ranging applications across a wide range of sectors, such as creating realistic images, writing natural language texts, composing music, and enabling creative design tasks. Our discussion also includes potential future research and development directions along with the challenges and ethical considerations associated with generative AI. A comprehensive overview of generative AI is provided in this review for researchers, practitioners, and enthusiasts.