A media company wants to automatically generate captions for video content. The captions must be synchronized with the audio. Which GenAI capability is most appropriate?

Text summarization to condense the video script

Speech-to-text transcription with timestamping

Text-to-image generation to create caption graphics

Code generation to write a video player

A developer is building a real-time translation app. The app sends short phrases to a foundation model and displays the translation. The team wants to minimize latency and cost. Which strategy is most effective?

Use a large model with high temperature for more accurate translations

Request the model to generate multiple translations and pick the best

Send the entire conversation history with every request

Keep prompts short and use a smaller, faster model for simple translations

A company is designing an AI system that researches a topic, writes a report, and then emails it to stakeholders. The system uses multiple agents. Which communication pattern is most appropriate?

A broadcast pattern where every agent receives all messages

All agents working in parallel and combining outputs at the end

A single agent that performs all steps without communication

A sequential workflow where the research agent passes results to the writing agent, which passes the report to the email agent

A developer is building a text-generation application that must answer questions about a company's internal HR policies. The policies are stored in a vector database. The developer wants to improve answer accuracy by providing the model with relevant context. Which technique should the developer use?

Randomly select policy sections to include in the prompt

Convert the user question into an embedding and retrieve similar policy chunks from the vector database

Use a larger model to memorize the policies during inference

Send the entire HR policy manual as a single prompt

A company wants to build a model that generates legal contract summaries. They have a large corpus of legal documents but limited compute budget. The team is deciding between fine-tuning a foundation model and using prompt engineering with retrieval. Which consideration is most important?

Fine-tuning always produces better results than retrieval-based prompting

Retrieval-based prompting cannot handle legal terminology

Fine-tuning eliminates the need for evaluation

Fine-tuning requires significant compute and a curated dataset, while retrieval-based prompting is faster to implement

AWSCertified AI Practitioner

Domain 2Objective 1

Task Statement 2.1: Explain the Basic Concepts of Generative AI (GenAI). AIF-C01 Practice Questions (Page 6)

Part of the Content Domain 2: Fundamentals of GenAI domain, which makes up ~19% of our current practice bank. AWS does not publish an official question count, but from its 90-minute exam (~35–60 total, ~7–11 in this domain), expect 2–4 from this objective — we provide 32 practice questions to prepare you well beyond it. (estimate)

32questions here

7free pages

6concepts

Questions 26–30

26application · easy
A media company wants to automatically generate captions for video content. The captions must be synchronized with the audio. Which GenAI capability is most appropriate?
Select an answer first
27application · medium
A developer is building a real-time translation app. The app sends short phrases to a foundation model and displays the translation. The team wants to minimize latency and cost. Which strategy is most effective?
Select an answer first
28application · medium
A company is designing an AI system that researches a topic, writes a report, and then emails it to stakeholders. The system uses multiple agents. Which communication pattern is most appropriate?
Select an answer first
29application · medium
A developer is building a text-generation application that must answer questions about a company's internal HR policies. The policies are stored in a vector database. The developer wants to improve answer accuracy by providing the model with relevant context. Which technique should the developer use?
Select an answer first
30expert · hard
A company wants to build a model that generates legal contract summaries. They have a large corpus of legal documents but limited compute budget. The team is deciding between fine-tuning a foundation model and using prompt engineering with retrieval. Which consideration is most important?
Select an answer first

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