There are several generative AI models currently in use, including Generative Adversarial Networks (GANs), transformer-based models such as Generative Pre-Trained GPT language models, and Markov models. GANs and transformer-based models are two of the most widely used generative AI models. GANs can create visual and multimedia artifacts from imagery and textual input data, while transformer-based models can generate textual content leveraging information from a vast amount of data. Markov models, an early example of generative AI, are named for Andrey Markov and have long been used for next-word prediction tasks like language modeling. These models are used in a variety of domains, including image and text generation, speech recognition, and natural language processing. The latest advancements in large generative models allow for the processing of enormous amounts of data, making it possible to feed these models vast amounts of information, including the entirety of the internet.