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Generative AI Foundations – Diffusion, Attention, and Creative Systems

Lesson 3: Attention, Conditioning, and Prompt Control

Lesson Objectives

By the end of this lesson, students should be able to:

  • Explain attention as a way of connecting relevant parts of input.
  • Describe conditioning in practical prompt terms.
  • Use negative constraints and references responsibly.

Lesson Content

Attention helps models connect parts of an input. In text, it helps relate words across a sentence or document. In image or multimodal generation, related ideas can influence subject, composition, style, and details.

Conditioning means steering generation with information: prompt text, example image, style reference, mask, layout, audio sample, or other control. Conditioning is powerful, but it is not absolute control. The model may overemphasize one detail, miss another, or combine ideas in strange ways.

A professional workflow uses clear positive instructions and clear negative constraints. It also respects rights and privacy. A reference should not be used to imitate a living person, copy protected artwork, or imply endorsement.

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