Generative AI is a subset of artificial intelligence focused on generating content or data by learning patterns and structures from existing data. It can create text, images, music and more with minimal human intervention. Generative AI models mimic human-like creativity and can adapt to a range of tasks. Generative AI is different from traditional AI models because it creates entirely new data based on the patterns it has learned rather than just processing and analyzing data. Some popular generative AI models include Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based models. The history of generative AI dates back to the 1950s and has evolved gradually with the development of neural networks in the 1980s and 1990s, leading to the emergence of more sophisticated generative models. Neural networks are the backbone of many generative AI models and consist of interconnected nodes or neurons.