A municipal greenhouse wants three things: a place to train and host a custom wilt model, an API that already serves foundation models without that training job, and dashboards so the director can see weekly detection counts. Which mapping is accurate?
Select an answer to reveal the explanation.
Short Explanation
Think of three different shops. SageMaker AI is the custom kitchen (train and host the wilt model). Bedrock is the ready-made counter (consume foundation models). Quick is the wall chart (weekly counts). Do not swap those counters.
Full Explanation
Amazon SageMaker AI is the practitioner match for training and hosting a custom model. Amazon Bedrock is the match for consuming foundation models without that training job. Amazon Quick is the match for analytics and visibility. Swapping those jobs, or inventing another training service, is outside the exam's service-to-job map.