Foundations · beginner
Generative AI (GenAI)
Generative AI refers to models that produce new content — text, images, audio, video, or code — rather than classifying or predicting from a fixed set of labels.
Explanation
Classification models answer "what is this?" — generative models answer "make me something." LLMs generate text. Diffusion models generate images. Audio models generate speech and music.
The category exploded in public awareness in late 2022 with ChatGPT and Stable Diffusion. Underneath, "generative AI" is a marketing umbrella over several distinct architectures (transformers for text, diffusion for images, etc.) that share an output rather than a method.
Generative AI products are sold by token, by image, or by API call, and have spawned a new class of cost-control concerns (see tokenizer and context window).
Examples
- ChatGPT writing an email.
- Midjourney creating an image from a prompt.
- GitHub Copilot suggesting code.
Frequently asked
What is Generative AI?
Generative AI refers to models that produce new content — text, images, audio, video, or code — rather than classifying or predicting from a fixed set of labels.
What is an example of generative ai?
ChatGPT writing an email.
How is Generative AI related to Large Language Model?
Generative AI and Large Language Model are both foundations concepts. A large language model is a neural network trained on huge amounts of text to predict the next token in a sequence. GPT-4, Claude, and Gemini are all LLMs.
Is Generative AI considered beginner?
Generative AI is generally considered beginner-level material in the AI and LLM space.