Home / AWS Certified AI Practitioner (AIF-C01) / 2 Practice / AWS-AIF-494
Images and text are sent to a model.
Control format and quality.
Choose two practices.
Hint 1: Focus on the requirement Validate modality format, quality, size, alignment, sensitivity, and model support before relying on combined inputs.
Hint 2: Key terms Review multimodal input preparation.
Multimodal inputA request containing more than one data modality, such as text and image.
Input alignmentThe correspondence between related values or regions across input modalities.
ResolutionThe amount of spatial or temporal detail represented in an image or signal.
Media qualityThe clarity, completeness, and validity of an image, audio, or other media input. × Incorrect Match format, resolution, audio quality, language, order, and size to model requirements and check missingness, alignment, quality, and personal data.
Detailed explanation A Incorrect Upload success proves the image format and quality are suitable
Requirements may still fail.
B Correct Match image or audio format, resolution, quality, language, order, and size to model requirements
Interpretation is more stable.
C Correct Check blur, missingness, cross-modal alignment, personal data, and representative cases
Quality and privacy are tested.
D Incorrect Personal data in an image needs no review
Images can contain sensitive data.
Check official documentation Compare the following points with the official documentation.
AWS公式AIF-C01 Domain 2.1のマルチモーダルモデル、入力形式、プライバシーを確認する。
Official references Official documentation 1 Official documentation 2 What to confirm 画像・音声・文章の入力条件と、品質・個人情報の検査を設計できる。
Key points Multimodal Input quality Personal data Notes Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認 Compare the definition with the AIF-C01 objective and the service documentation before applying it. Keep the concept separate from a particular answer choice or implementation step. Foundation review Multimodal input A request containing more than one data modality, such as text and image.
Input alignment The correspondence between related values or regions across input modalities.
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