What it covers
The official exam guide breaks this domain into 3 objectives:
- Explain the basic concepts of generative AI
- Understand the capabilities and limitations of generative AI for solving business problems
- Describe AWS infrastructure and technologies for building generative AI applications
Practice this domain
A drill pulls every published question in this domain and grades each one as you go. Flashcards skip the grading entirely — read the stem, flip when you're ready, move on.
A sample question
What most clearly distinguishes generative AI from traditional predictive machine learning?
- AGenerative AI requires no data at all, while predictive ML requires data.
- BGenerative AI runs only on premises, while predictive ML runs only in cloud.
- CGenerative AI creates new content, while predictive ML outputs a prediction.
- DGenerative AI and predictive ML are simply two names for the same approach.
Generative AI produces new content such as text or images, whereas predictive ML outputs a classification, number, or grouping. Both depend on data, both run in either environment, and they are genuinely different approaches.
Kiro is an AWS offering associated with which activity?
- AAI-assisted software development work carried out by engineering teams.
- BArchiving rarely accessed records at the lowest available storage cost.
- CDistributing incoming network traffic across several virtual servers.
- DRecording every API call made within an AWS account for later auditing.
Kiro relates to AI-assisted software development. Archival storage, load balancing, and API auditing are handled by S3 Glacier, Elastic Load Balancing, and CloudTrail respectively.
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