A company is building a customer-support chatbot that must respond in both English and Spanish. The team has a limited budget and needs low-latency responses. They have already collected a small set of example conversations for few-shot prompting. Which model selection and configuration approach best meets these requirements?

Select a model with the longest input/output length, regardless of language support, and use zero-shot prompting.

Select the smallest model that supports both languages, use few-shot examples, and set a low temperature for consistent answers.

Select a model that only supports English, and plan to translate responses to Spanish using a separate translation service.

Select the largest model available to ensure high accuracy, and set a high temperature to encourage creative responses.

A company wants to build a question-answering system over their internal wiki. They plan to use Amazon Bedrock Knowledge Bases. What is the primary benefit of using RAG instead of fine-tuning the model on the wiki content?

RAG allows the model to access the latest information without retraining.

RAG eliminates the need for a vector database.

RAG guarantees that the model will never hallucinate.

RAG is always cheaper than fine-tuning.

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Domain 3Objective 1

Task Statement 3.1: Describe Design Considerations for Applications That Use Foundation Models (FMs). AIF-C01 Practice Questions (Page 4)

Part of the Content Domain 3: Applications of Foundation Models domain, which makes up ~32% of our current practice bank. AWS does not publish an official question count, but from its 90-minute exam (~35–60 total, ~11–19 in this domain), expect 3–5 from this objective — we provide 29 practice questions to prepare you well beyond it. (estimate)

29questions here

6free pages

6concepts

Questions 16–20

16application · medium
A company is building a customer-support chatbot that must respond in both English and Spanish. The team has a limited budget and needs low-latency responses. They have already collected a small set of example conversations for few-shot prompting. Which model selection and configuration approach best meets these requirements?
Select an answer first
17foundation · easy
Which AWS service is specifically designed to implement RAG by providing a managed knowledge base for foundation models?
Select an answer first
18application · medium
A developer is using a foundation model to generate product descriptions. They want the descriptions to be consistent in tone and style. Which inference parameter should they set to a low value?
Select an answer first
19application · medium
A company wants to build a question-answering system over their internal wiki. They plan to use Amazon Bedrock Knowledge Bases. What is the primary benefit of using RAG instead of fine-tuning the model on the wiki content?
Select an answer first
20foundation · easy
Which AWS service is commonly used as a vector database to store and search embeddings for RAG applications?
Select an answer first

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Task Statement 3.1: Describe Design Considerations for Applications That Use Foundation Models (FMs). AIF-C01 Practice Questions (Page 4)

Questions 16–20

Which AWS service is specifically designed to implement RAG by providing a managed knowledge base for foundation models?

A developer is using a foundation model to generate product descriptions. They want the descriptions to be consistent in tone and style. Which inference parameter should they set to a low value?

A company wants to build a question-answering system over their internal wiki. They plan to use Amazon Bedrock Knowledge Bases. What is the primary benefit of using RAG instead of fine-tuning the model on the wiki content?

Which AWS service is commonly used as a vector database to store and search embeddings for RAG applications?

Keep studying — Content Domain 3: Applications of Foundation Models