What's changed: Added per-section figures (cert-figure-retrofit). Rewrote AI-103 Chapter 4 to align with official skills measured (Apr 16, 2026). Shifted from AI-102-style (prebuilt Vision + Custom Vision) to a generation-centric design: s1 = image/video generation and editing (text→image: GPT-image-1/DALL·E, inpainting = mask editing, reference media, generation/editing controls, text→video: Sora, async); s2 = multimodal understanding (captions/visual QA/alt-text/object & region ID) + Content Understanding visual characteristic extraction (single-task/pro-mode, video analysis) + multimodal Responsible AI (Content Safety image moderation, indirect prompt injection via in-image text, visual policy: watermarks/prohibited symbols/brand)
4.1Image and Video Generation and Editing
In AI-103, computer vision centers on generation more than recognition. Understand—from a developer’s view—deploying image- and video-generation models in Microsoft Foundry, generating images and videos from text prompts and reference media, and editing them via mask-based inpainting and prompt-driven changes.
In AI-102, computer vision centered on recognizing images (classification, object detection, OCR). AI-103 shifts the center to generating and editing images and videos and flexibly understanding them with multimodal models. This section covers generation and editing. You implement it in Microsoft Foundry by selecting image-generation and video-generation models from the catalog, deploying them, and calling them via SDK/REST. Auth uses managed identity (keyless) as in Chapter 1.
4.1.1Image generation (text → image)
Image generation creates new images from a text prompt (e.g., "a dog walking on a beach at dusk, watercolor style"). In Foundry you deploy and use image-generation models such as GPT-image-1 or DALL·E. Beyond the prompt, you can pass reference media (a reference image) to guide style or composition. You tune output with generation controls (image size, quality, number of images n, etc.). The key difference from pre-AI-102 vision is that you create images anew rather than recognize existing ones.
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