A Bedrock team wants an Amazon-offered foundation-model family for text or multi-modal work and must not invent a fictional AWS model name. Which in-scope family can they recognize?
Select an answer to reveal the explanation.
Short Explanation
Think of recognizing the AWS family on the exam list. Amazon Nova is that foundation-model family. Quick is a dashboard, Transcribe is speech-to-text, and made-up SKUs are out of scope.
Full Explanation
At practitioner level, the in-scope Amazon-offered foundation-model family to recognize for text or multi-modal work is Amazon Nova. That recognition task is about matching a real AWS FM family name on the exam list, not inventing product labels or confusing adjacent AWS AI services with foundation-model families. Nova fits the ask because it is the Amazon-offered FM family presented for that recognition, covering the kinds of generative workloads the question frames.
A made-up AWS SKU fails because inventing model names is out of scope; the exam expects known in-list families, not creative labeling. Amazon Quick fails because it is an analytics and dashboard experience, not a foundation-model family for generative text or multi-modal generation. Amazon Transcribe fails because speech-to-text is a specialized AI service, not an FM family used as a general prompted generative model catalog entry.
Exam caveat: adjacent AWS AI and analytics products are common distractors; being able to name the FM family versus transcription, dashboards, or invented SKUs is the discrimination the question is testing. Operational check: when a Bedrock team shortlists Amazon-offered models, verify the family against current AWS documentation and the approved Region’s model list, and reject any name that cannot be shown as an in-scope FM family.