試験Generative-AI-Leader トピック3 問題20 スレッド
Google Generative-AI-Leaderのリアル試験問題集
問題 #: 20
トピック #: 3
問題 #: 20
トピック #: 3
A boutique sneaker label plans to use generative AI to render concept images for upcoming footwear lines. They can choose between a compact and carefully curated set of about 15,000 images of their own past collections and a very large and mixed set of roughly 2.2 million generic footwear photos from public sources. If they prioritize the smaller curated set of their proprietary designs as the primary training data, what outcome should they expect from the resulting model?
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Prioritizing a smaller but curated set of proprietary images makes the model learn the label's distinctive patterns, motifs, and color relationships more strongly. The training signal concentrates on consistent brand examples, so the generator better reproduces the brand's aesthetic and design language. Because the data distribution is narrower than a large mixed corpus, the model tends to explore fewer directions and may trade off breadth of styles for fidelity to the brand identity.
Miyawaki 2026-04-23 11:12:21
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