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Free Amazon AIF-C01 Exam Questions (page: 11)

Page 11 of 68
PDF with 334 Questions

A company wants to use large language models (LLMs) with Amazon Bedrock to develop a chat interface for the company's product manuals. The manuals are stored as PDF files.

Which solution meets these requirements MOST cost-effectively?

  1. Use prompt engineering to add one PDF file as context to the user prompt when the prompt is submitted to Amazon Bedrock.
  2. Use prompt engineering to add all the PDF files as context to the user prompt when the prompt is submitted to Amazon Bedrock.
  3. Use all the PDF documents to fine-tune a model with Amazon Bedrock. Use the fine-tuned model to process user prompts.
  4. Upload PDF documents to an Amazon Bedrock knowledge base. Use the knowledge base to provide context when users submit prompts to Amazon Bedrock.

Answer(s): D

Explanation:

Using an Amazon Bedrock knowledge base allows the model to efficiently access relevant information from the PDF manuals when needed, reducing the cost compared to continuously fine-tuning a model or providing all PDFs as context in each prompt. This approach ensures that only necessary context is provided, making it cost-effective.



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

Answer(s): D

Explanation:

Benchmark datasets are standardized datasets specifically designed for evaluating models for bias and fairness, allowing for efficient assessment with minimal administrative effort. The other options would require more manual processing and might not provide a consistent basis for evaluating bias and discrimination.



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.

Answer(s): C

Explanation:

Creating effective prompts helps guide the pre-trained generative AI model to produce content that aligns with the company's brand voice and messaging. The other options either involve model architecture changes or require extensive training, which are not necessary for aligning content generation.



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.

Answer(s): A,C

Explanation:

Detect imbalances or disparities in the data: Identifying and addressing data imbalances helps minimize biases that could negatively affect customers.
Evaluate the model's behavior so that the company can provide transparency to stakeholders:
Evaluating the model and ensuring transparency is important for responsible AI usage, as it helps stakeholders understand how decisions are made.
The other options are either not directly related to minimizing bias or do not address responsible AI development.



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.

Answer(s): A



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