Generative AI works by utilizing deep learning techniques, such as neural networks and probabilistic models. These algorithms are trained on large datasets to learn patterns and capture the underlying structure of the data. Once trained, the generative AI model can generate new content by sampling from the learned distribution, allowing it to create unique and creative outputs.

Generative AI has various applications across different industries. Some examples include: Data augmentation: Generating synthetic data to augment training datasets. Virtual reality: Creating immersive virtual environments. Gaming: Generating game levels, characters, or storylines. Personalized recommendations: Generating personalized recommendations for products or services.

Generative AI is a specific branch of artificial intelligence that focuses on creating new content by learning patterns from existing data. It differs from other types of AI, such as predictive or classification models, which aim to make predictions or classify data based on known patterns. Generative AI is more concerned with creativity, imagination, and generating novel outputs.