A support feature drafts a reply to a customer message.
A separate model labels the message as urgent or normal.
Which output is a representative generative-AI output?
Generating a new reply is a generative task; predicting a fixed label is classification.
Detailed explanation
The model creates new text from the input, which is a generative use case.
The model creates new text from the input, which is a generative use case.
Assigning a predefined class is classification.
Assigning a predefined class is classification.
This is a database integrity feature, not model content generation.
This is a database integrity feature, not model content generation.
This is an infrastructure monitoring result, not generated content.
This is an infrastructure monitoring result, not generated content.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01ガイドのDomain 2.1で生成AIの定義とユースケースを確認する。Expected result
新しいコンテンツ生成と、分類・制約検査・監視の出力を区別できる。Key points
- New content
- Generation versus classification
- Business assistance
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
- Command output formatting can vary slightly by distribution or tool version.
- Run the example in a temporary directory or process when possible.
Foundation review
Read the scope first
Check whether the command acts on the current shell, a new process, an existing process, or a file.
Verify the observable result
Use the supplied command and compare the output with the expected result.