Glossary term
Glossary term
Foundations
Generative AI refers to systems that create content like text, images, or code by learning patterns from data, generating new, dynamic output in real time rather than selecting from pre-set options.
An emerging transformative field with no formal definition. That said, most experts agree that generative AI models can create ("generate") content that is all of the following:
complex
coherent
original
Examples of generative AI include:
Large language models, which can generate sophisticated original text and answer questions.
Image generation model, which can produce unique images.
Audio and music generation models, which can compose original music or generate realistic speech.
Video generation models, which can generate original videos.
Some earlier technologies, including LSTMs and RNNs, can also generate original and coherent content. Some experts view these earlier technologies as generative AI, while others feel that true generative AI requires more complex output than those earlier technologies can produce.
Contrast with predictive ML.
OpenAI ChatGPT, Anthropic Claude, and Google Gemini are flagship generative AI text products.
Midjourney, Stable Diffusion, and Black Forest Labs FLUX generate images from text prompts.
GitHub Copilot, Cursor, and Replit Agent use generative AI to write production code.
Created for this library
A marketing team uses generative AI to draft email subject lines and visuals that creative leads then edit and approve.
A consulting firm builds a generative AI practice that helps clients identify and prioritize use cases beyond the first chatbot.
A bank pilots generative AI in its internal knowledge management so analysts can summarize long policy documents quickly.
Definition source: Google for Developers Machine Learning Glossary | Creative Commons Attribution 4.0 License