Generative AI Models and Techniques

Generative AI refers to a class of models capable of creating new data from a given distribution. These models can generate diverse forms of data, including text, images, audio, and videos. The key techniques in generative AI include Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based models like GPT. This paper explores the underlying principles of these generative techniques, their applications in various fields, and their current challenges. We will review the significant advancements in these areas, compare different generative methods, and discuss future directions for enhancing the quality and applicability of generative models.