Generative AI models mostly use **Artificial Neural Networks**. Specifically, architectures such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) are popular examples of generative models that leverage neural networks to create new data samples that resemble a training dataset. While decision trees, clustering, and Support Vector Machines (SVMs) are useful in various machine learning tasks, they are not predominantly