AIF-C01 practice questions 171–180

1. Question 171 · 417 in bank

   A company designed an AI-powered agent to answer customer inquiries based on product manuals. Which strategy can improve customer confidence levels in the AI-powered agent's responses?

   • AWriting the confidence level in the response
   • BIncluding referenced product manual links in the response
   • CDesigning an agent avatar that looks like a computer
   • DTraining the agent to respond in the company's language style

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   Answer: B

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2. Question 172 · 417 in bank

   A hospital developed an AI system to provide personalized treatment recommendations for patients. The AI system must provide the rationale behind the recommendations and make the insights accessible to doctors and patients. Which human-centered design principle does this scenario present?

   • AExplainability
   • BPrivacy and security
   • CFairness
   • DData governance

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   Answer: A

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3. Question 173 · 417 in bank

   Which statement presents an advantage of using Retrieval Augmented Generation (RAG) for natural language processing (NLP) tasks?

   • ARAG can use external knowledge sources to generate more accurate and informative responses.
   • BRAG is designed to improve the speed of language model training.
   • CRAG is primarily used for speech recognition tasks.
   • DRAG is a technique for data augmentation in computer vision tasks.

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   Answer: A

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4. Question 174 · 417 in bank

   A company has created a custom model by fine-tuning an existing large language model (LLM) from Amazon Bedrock. The company wants to deploy the model to production and use the model to handle a steady rate of requests each minute. Which solution meets these requirements MOST cost-effectively?

   • ADeploy the model by using an Amazon EC2 compute optimized instance.
   • BUse the model with on-demand throughput on Amazon Bedrock.
   • CStore the model in Amazon S3 and host the model by using AWS Lambda.
   • DPurchase Provisioned Throughput for the model on Amazon Bedrock.

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   Answer: D

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5. Question 175 · 417 in bank

   Which technique involves training AI models on labeled datasets to adapt the models to specific industry terminology and requirements?

   • AData augmentation
   • BFine-tuning
   • CModel quantization
   • DContinuous pre-training

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   Answer: B

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6. Question 176 · 417 in bank

   A company is creating an agent for its application by using Amazon Bedrock Agents. The agent is performing well, but the company wants to improve the agent’s accuracy by providing some specific examples. Which solution meets these requirements?

   • AModify the advanced prompts for the agent to include the examples.
   • BCreate a guardrail for the agent that includes the examples.
   • CUse Amazon SageMaker Ground Truth to label the examples.
   • DRun a script in AWS Lambda that adds the examples to the training dataset.

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   Answer: A

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7. Question 177 · 417 in bank

   Which option is a benefit of using infrastructure as code (IaC) in machine learning operations (MLOps)?

   • AIaC eliminates the need for hyperparameter tuning.
   • BIaC always provisions powerful compute instances, contributing to the training of more accurate models.
   • CIaC streamlines the deployment of scalable and consistent ML workloads in cloud environments.
   • DIaC minimizes overall expenses by deploying only low-cost instances.

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   Answer: C

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8. Question 178 · 417 in bank

   A company wants to fine-tune a foundation model (FM) to answer questions for a specific domain. The company wants to use instruction-based fine-tuning. How should the company prepare the training data?

   • AGather company internal documents and industry-specific materials. Merge the documents and materials into a single file.
   • BCollect external company reviews from various online sources. Manually label each review as either positive or negative.
   • CCreate pairs of questions and answers that specifically address topics related to the company's industry domain.
   • DCreate few-shot prompts to instruct the model to answer only domain knowledge.

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   Answer: C

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9. Question 179 · 417 in bank

   Which ML technique ensures data compliance and privacy when training AI models on AWS?

   • AReinforcement learning
   • BTransfer learning
   • CFederated learning
   • DUnsupervised learning

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   Answer: C

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10. Question 180 · 417 in bank

    A manufacturing company has an application that ingests consumer complaints from publicly available sources. The application uses complex hard-coded logic to process the complaints. The company wants to scale this logic across markets and product lines. Which advantage do generative AI models offer for this scenario?

    • APredictability of outputs
    • BAdaptability
    • CLess sensitivity to changes in inputs
    • DExplainability

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    Answer: B

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AIF-C01 practice, question 171. 417 questions available.