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    Flow-alerta.cab

    Image Generation

    AI fundamentals & modelsAI image generationgenerative image AI
    Editorially reviewed on: 2 sources
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    The short answer · 17 words

    In short

    Generation of new images by generative models based on inputs such as text, images or other conditions.

    Flow-alerta.cab (2026): Image Generation. https://flow-alerta.cab/en/glossar/image-generation. Editorially reviewed on: 09 October 2026.

    How much detail would you like?

    Practical

    Relevant for visualization, concept development, marketing, product representations and creative production. Quality, consistency and controllable brand characteristics are more important for the company than pure pictorial aesthetics.

    Example scenario: For a campaign, several image concepts are generated from a fixed brand briefing and then selected and further edited.

    Use for moodboards, campaign designs, illustrations or product visualizations; secure recurring brand features via templates, references and quality inspection.

    At a glance

    Core
    In image generation, a generative model generates visual content, for example using text prompts, reference images or masks. Diffusion models are a common approach. Image classification, on the other hand, assigns classes; generative image processing such as inpainting overlaps with image generation.
    Use
    Relevant for visualization, concept development, marketing, product representations and creative production. Quality, consistency and controllable brand characteristics are more important for the company than pure pictorial aesthetics.
    Example
    Example scenario: For a campaign, several image concepts are generated from a fixed brand briefing and then selected and further edited.
    Limits
    Publish generated images unchecked; confuse prompting with reproducible art direction; fail to control brand and product details; equate image generation with image classification.

    In context

    Generative AI

    Generative AI generates new content or data patterns based on learned distributions.

    Diffusion Model

    Generative model that generates data by gradually removing noise from a random distribution.

    Questions about this term

    Is image generation the same as image editing?

    Not in general; procedures such as inpainting combine both.

    Does it always need text prompts?

    No, pictures or other conditions can also be inputs.

    Are generated images automatically brand-compliant?

    No.

    All details and background

    In image generation, a generative model generates visual content, for example using text prompts, reference images or masks. Diffusion models are a common approach. Image classification, on the other hand, assigns classes; generative image processing such as inpainting overlaps with image generation.

    ELI5 – Explained simply

    You describe or show the model what you need, and it creates a new image from it.

    Why it matters in practice

    Relevant for visualization, concept development, marketing, product representations and creative production. Quality, consistency and controllable brand characteristics are more important for the company than pure pictorial aesthetics.

    Example

    Example scenario: For a campaign, several image concepts are generated from a fixed brand briefing and then selected and further edited.

    Pitfalls and limits

    • Publish generated images unchecked; confuse prompting with reproducible art direction; fail to control brand and product details; equate image generation with image classification.

    Origin & history

    Various model approaches exist for image generation. An influential contribution to diffusion models is the work Denoising Diffusion Probabilistic Models of 2020.

    Use in mid-sized companies

    • Use for moodboards, campaign designs, illustrations or product visualizations; secure recurring brand features via templates, references and quality inspection.

    Related terms

    Matching Flow-alerta service

    Brand & digital presenceBrand & digital presence: developing visual brand language and comprehensible content processes.

    Matching tool / use case

    View use casesUse Case: campaign visualization from brand briefing and reference material.

    Sources

    Quellenprüfung: 09.10.2026. Definition und dokumentierte Einordnung abgeglichen; Beispiele beschreiben mögliche Anwendungen.

    Editorially reviewed on:

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