Definition
Generative AI is AI that creates new content, such as text, images, audio, video or computer programs, by learning patterns from existing examples. Predictive AI assigns a label or number to an input, while generative AI produces something new that resembles what it learned from.
In simple words
A predictive model looks at a photo and says "cat". A generative model takes the word "cat" and draws a new one. It's like a student who has read so many stories that they can write a new one in the same style. It doesn't paste from a store of stories, but it can sometimes repeat what it saw.
Why it matters
It has changed how people write, build software, design and search. It's useful, and it's risky: it can be wrong in a confident tone, raises copyright questions, and makes deepfakes easy. Anyone using or building it should understand both sides.
How it works
| Makes | Main technique | Example tools |
|---|---|---|
| Text, computer programs | Large language models | ChatGPT, Claude, Gemini, Llama |
| Images | Diffusion models | Stable Diffusion, Midjourney |
| Audio, music | Diffusion and Transformer models | ElevenLabs, Suno |
| Video | Video diffusion models | Sora, Veo |
Predictive vs generative
A predictive model learns the chance of a label given the input. A generative model learns the patterns of the data itself, so it can sample new examples from what it learned.
Try it yourself
How a new picture is made
It doesn't look up an existing picture. Watch where the new one comes from.
Predictive or generative?
A predictive model gives a label or a number. A generative model produces something new. Which is each one?
Making a song from one line of description
Writing a poem about the monsoon
Looking at a photo and saying "cat"
Estimating the price of a house
Marking an email as spam or not
Drawing a new cat from the word "cat"
Common mistakes
- Thinking it looks up answers. It generates them, unless connected to a search or document tool.
- Sharing private company or personal data with public tools without checking their data policy.
Check yourself
Summary
- Generative AI creates new content, by learning from examples.
- LLMs make text, and diffusion models make images.
- Output can be wrong, so check what matters.
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