AWS Certified AI Practitioner AIF-C01 Practice Test

AWS Certified AI Practitioner AIF-C01 Practice Test practice questions, page 17 of 20, with answer review and explanations.

Question 81

A social media company wants to use a large language model (LLM) for content moderation. The company wants to evaluate the LLM outputs for bias and potential discrimination against specific groups or individuals. Which data source should the company use to evaluate the LLM outputs with the LEAST administrative effort?

  1. User-generated content
  2. Moderation logs
  3. Content moderation guidelines
  4. Benchmark datasets

Question 82

A company wants to use a pre-trained generative AI model to generate content for its marketing campaigns. The company needs to ensure that the generated content aligns with the company's brand voice and messaging requirements. Which solution meets these requirements?

  1. Optimize the model's architecture and hyperparameters to improve the model's overall performance.
  2. Increase the model's complexity by adding more layers to the model's architecture.
  3. Create effective prompts that provide clear instructions and context to guide the model's generation.
  4. Select a large, diverse dataset to pre-train a new generative model.

Question 83

A loan company is building a generative AI-based solution to offer new applicants discounts based on specific business criteria. The company wants to build and use an AI model responsibly to minimize bias that could negatively affect some customers. Which actions should the company take to meet these requirements? (Choose two.)

  1. Detect imbalances or disparities in the data.
  2. Ensure that the model runs frequently.
  3. Evaluate the model's behavior so that the company can provide transparency to stakeholders.
  4. Use the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) technique to ensure that the model is 100% accurate.
  5. Ensure that the model's inference time is within the accepted limits.

Question 84

A company is using an Amazon Bedrock base model to summarize documents for an internal use case. The company trained a custom model to improve the summarization quality. Which action must the company take to use the custom model through Amazon Bedrock?

  1. Purchase Provisioned Throughput for the custom model.
  2. Deploy the custom model in an Amazon SageMaker endpoint for real-time inference.
  3. Register the model with the Amazon SageMaker Model Registry.
  4. Grant access to the custom model in Amazon Bedrock.

Question 85

A company needs to choose a model from Amazon Bedrock to use internally. The company must identify a model that generates responses in a style that the company's employees prefer. What should the company do to meet these requirements?

  1. Evaluate the models by using built-in prompt datasets.
  2. Evaluate the models by using a human workforce and custom prompt datasets.
  3. Use public model leaderboards to identify the model.
  4. Use the model InvocationLatency runtime metrics in Amazon CloudWatch when trying models.