Amazon AIF-C01 Online Practice Questions and Exam Preparation

Amazon AIF-C01 Online Questions & Answers

• Question 121:

  HOTSPOT

  A company is building a generative AI application and is reviewing foundation models (FMs). The company needs to consider multiple FM characteristics.

  Select the correct FM characteristic from the following list for each definition. Each FM characteristic should be selected one time.

  

  

  Explanation:

  Amount of information that can fit in a single prompt -> Context windows Length of time it takes for a model to generate an output -> Latency Multiple users invoking an application endpoint simultaneously -> Concurrency

  Context windows determine how much information the model can process at once.

  Latency is the response time for generating output.

  Concurrency measures how many users or requests the endpoint can handle at the same time.

• Question 122:

  A company wants to deploy a conversational chatbot to answer customer questions. The chatbot is based on a fine-tuned Amazon SageMaker JumpStart model. The application must comply with multiple regulatory frameworks. Which capabilities can the company show compliance for? (Select TWO.)

  A. Auto scaling inference endpoints
  B. Threat detection
  C. Data protection
  D. Cost optimization
  E. Loosely coupled microservices
  B. Threat detection
  C. Data protection

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  To comply with multiple regulatory frameworks, the company must ensure data protection and threat detection. Data protection involves safeguarding sensitive customer information, while threat detection identifies and mitigates security threats to the application.

  Option C (Correct): "Data protection":This is correct because data protection is critical for compliance with privacy and security regulations.

  Option B (Correct): "Threat detection":This is correct because detecting and mitigating threats is essential to maintaining the security posture required for regulatory compliance.

  Option A:"Auto scaling inference endpoints" is incorrect because auto-scaling does not directly relate to regulatory compliance.

  Option D:"Cost optimization" is incorrect because it is focused on managing expenses, not compliance.

  Option E:"Loosely coupled microservices" is incorrect because this architectural approach does not directly address compliance requirements.

  References:

  AWS Compliance Capabilities:AWS offers services and tools, such as data protection and threat detection, to help companies meet regulatory requirements for security and privacy.

• Question 123:

  A research team wants to evaluate multiple foundation models using the same prompt set. The evaluation must include human scoring on output quality. Which solution should the team use?

  A. Amazon Comprehend
  B. Amazon OpenSearch vector search
  C. Amazon Bedrock model evaluation
  D. Amazon SageMaker Ground Truth Plus
  C. Amazon Bedrock model evaluation

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  Bedrock model evaluation supports human and automated scoring across multiple FMs. It allows teams to compare outputs, rate quality, and generate benchmark reports for model selection.

• Question 124:

  Which component of Amazon Bedrock Studio can help secure the content that AI systems generate?

  A. Access controls
  B. Function calling
  C. Guardrails
  D. Knowledge bases
  C. Guardrails

• Question 125:

  A company is using a large collection of web data to produce a large language model (LLM). The company completes a random initialization of the model's weights. Next, the company fits the model to the data through a language objective modelling function.

  Which stage of the model training process does this scenario describe?

  A. Fine-tuning
  B. Pre-training
  C. Model selection
  D. Deployment
  B. Pre-training

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  Explanation

  The model is being trained from randomly initialized weights on a large corpus using a general language modeling objective, which corresponds to the pre-training phase where foundational knowledge is learned.

• Question 126:

  A bank is building a chatbot to answer customer questions about opening a bank account. The chatbot will use public bank documents to generate responses. The company will use Amazon Bedrock and prompt engineering to improve the chatbot's responses. Which prompt engineering technique meets these requirements?

  A. Complexity-based prompting
  B. Zero-shot prompting
  C. Few-shot prompting
  D. Directional stimulus prompting
  C. Few-shot prompting

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  Few-shot prompting involves providing the generative AI model with several examples (drawn from public bank documents) to guide it in generating more accurate and relevant responses. This technique helps the chatbot better align its answers with the desired content and format.

• Question 127:

  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?

  A. Explainability
  B. Privacy and security
  C. Fairness
  D. Data governance
  A. Explainability

• Question 128:

  A company needs to apply numerical transformations to a set of images to transpose and rotate the images. Which solution will meet these requirements in the MOST operationally efficient way?

  A. Create a deep neural network by using the images as input.
  B. Create an AWS Lambda function to perform the transformations.
  C. Use an Amazon Bedrock large language model (LLM) with a high temperature.
  D. Use AWS Glue Data Quality to make corrections to each image.
  B. Create an AWS Lambda function to perform the transformations.

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  An AWS Lambda function can efficiently perform numerical image transformations such as transposing and rotating images at scale without the need to build or train a neural network, making it the most operationally efficient solution.

• Question 129:

  A company wants to fine-tune a foundation model (FM) for a specific use case. The company needs to deploy the FM on Amazon Bedrock for internal use.

  Which solution will meet these requirements?

  A. Run responses that have been generated by a pre-trained FM through Amazon Bedrock Guardrails to create the custom FM.
  B. Use Amazon Personalize to customize the FM with custom data.
  C. Use conversational builder for Amazon Bedrock Agents to create the custom model.
  D. Use Amazon SageMaker AI to customize the FM. Then, import the trained model into Amazon Bedrock.
  D. Use Amazon SageMaker AI to customize the FM. Then, import the trained model into Amazon Bedrock.

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  Explanation

  Amazon SageMaker AI provides full training and fine-tuning capabilities for foundation models using custom data, and the resulting trained model can then be imported and deployed in Amazon Bedrock for internal use.

• Question 130:

  A financial company is using ML to help with some of the company's tasks. Which option is a use of generative AI models?

  A. Summarizing customer complaints
  B. Classifying customers based on product usage
  C. Segmenting customers based on type of investments
  D. Forecasting revenue for certain products
  A. Summarizing customer complaints

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  Generative AI models are designed to generate new content such as text, images, or audio. Summarizing customer complaints involves generating concise versions of longer texts, which is a task well-suited for generative AI models like large language models.