Organize AI use cases.
Distinguish predicting known outcomes from creating new content.
Choose two appropriate mappings.
Use predictive models for labels or values and generative models for new text, images, code, or other content.
Detailed explanation
It estimates a known numeric or class outcome.
It estimates a known numeric or class outcome.
It creates new content from an input or instruction.
It creates new content from an input or instruction.
Generation is different from classification.
Generation is different from classification.
It needs features or other inputs to make a prediction.
It needs features or other inputs to make a prediction.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01試験ガイドDomain 1.1の予測AIと生成AIの違いを確認する。Expected result
予測と生成の目的・出力の違いを具体例で説明できる。Key points
- Prediction
- Generation
- Fit
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.