Generative AI refers to a class of artificial intelligence models and techniques that aim to create new content or generate new data samples that resemble the patterns or distribution of the input data. In response to prompts, the system can generate text, images, or other media. Generative models learn the underlying structure and characteristics of the data and use this knowledge to generate new examples that capture the essence of the input. 

Generative AI can be used in a wide range of applications, such as text generation, image synthesis, music composition, video generation, and more. Some popular techniques for generative AI include generative adversarial networks (GANs), variational autoencoders (VAEs), and autoregressive models such as language models. These techniques are typically based on deep learning architectures and require large amounts of data to train effectively.