The Six Generative AI Model Types & Real-World Use Cases
Understanding Generative AI Business Applications
When ChatGPT went mainstream about a year ago, it captured the world’s undivided attention. McKinsey estimates that generative AI may add up to four trillion dollars to the economy.[1] Generative AI has broken barriers and transformed how we think about what computers are truly capable of. No matter your role or skill level, everyone now has the potential to create text, code, images, audio, and video that is nearly indistinguishable from human-generated content. Using nothing more than an internet browser and your natural ability to ask questions, your creativity is no longer bounded by your innate skills. These questions, known as prompts, allow anyone to create prose, write code, compose songs, and generate art that the Old Masters would envy.
Unlike traditional AI, which deals primarily with numeric data and occasionally small amounts of text, generative AI refers to a category of AI systems capable of generating completely novel content on their own. Unlike most AI systems (sometimes called predictive AI), which focus on analyzing historical data and making future numeric predictions, generative AI allows computers to produce brand-new outputs that are often indistinguishable from human-generated content.
