Text is only one thing AI can generate. The same learning idea powers images, speech, music, and video, with different ways of representing the data.
Images from noise
Many image generators use a diffusion approach. During training, the system learns how to remove noise from pictures. To create a new image, it starts with random noise and removes it step by step, guided by a text description, until a picture appears.
Audio and music
Sound can be treated as a sequence, much like text, or as a picture of frequencies over time. Models learn the patterns of speech or instruments and can then produce new samples, convert text to speech, or clone a voice from a recording.
Video
Video adds time. The model must keep objects consistent from frame to frame, which makes it harder than a single image, and results are still uneven.
Strengths and limits
- Fast ideation and variations for design, storytelling, and prototyping.
- Details can be wrong: extra fingers, garbled text, impossible shadows.
- Generated media can mislead when presented as real.
Using it responsibly
Check generated material before sharing it, label it when appropriate, and be careful with real people's likenesses and voices. Respect the rights of creators whose work may be involved.
Continue with the book
Explore the full treatment, worked examples, and exercises in AI Made Simple.
Adapted from AI Made Simple, published by Choral Software. Article text and original examples © 2026 Choral Software. All rights reserved.