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최신 AWS Certified AI AIF-C01 무료샘플문제 (Q230-Q235):

질문 # 230
A company wants to improve the accuracy of the responses from a generative AI application. The application uses a foundation model (FM) on Amazon Bedrock.
Which solution meets these requirements MOST cost-effectively?

A. Use prompt engineering.
B. Fine-tune the FM.
C. Retrain the FM.
D. Train a new FM.

정답：A

설명：
The company wants to improve the accuracy of a generative AI application using a foundation model (FM) on Amazon Bedrock in the most cost-effective way. Prompt engineering involves optimizing the input prompts to guide the FM to produce more accurate responses without modifying the model itself. This approach is cost- effective because it does not require additional computational resources or training, unlike fine-tuning or retraining.
Exact Extract from AWS AI Documents:
From the AWS Bedrock User Guide:
"Prompt engineering is a cost-effective technique to improve the performance of foundation models. By crafting precise and context-rich prompts, users can guide the model to generate more accurate and relevant responses without the need for fine-tuning or retraining." (Source: AWS Bedrock User Guide, Prompt Engineering for Foundation Models) Detailed Explanation:
* Option A: Fine-tune the FM.Fine-tuning involves retraining the FM on a custom dataset, which requirescomputational resources, time, and cost (e.g., for Amazon Bedrock fine-tuning jobs). It is not the most cost-effective solution.
* Option B: Retrain the FM.Retraining an FM from scratch is highly resource-intensive and expensive, as it requires large datasets and significant compute power. This is not cost-effective.
* Option C: Train a new FM.Training a new FM is the most expensive option, as it involves building a model from the ground up, requiring extensive data, compute resources, and expertise. This is not cost- effective.
* Option D: Use prompt engineering.This is the correct answer. Prompt engineering adjusts the input prompts to improve the FM's responses without incurring additional compute costs, making it the most cost-effective solution for improving accuracy on Amazon Bedrock.
References:
AWS Bedrock User Guide: Prompt Engineering for Foundation Models (https://docs.aws.amazon.com
/bedrock/latest/userguide/prompt-engineering.html)
AWS AI Practitioner Learning Path: Module on Generative AI Optimization Amazon Bedrock Developer Guide: Cost Optimization for Generative AI (https://aws.amazon.com/bedrock/)

질문 # 231
A global financial company has developed an ML application to analyze stock market data and provide stock market trends. The company wants to continuously monitor the application development phases and ensure that company policies and industry regulations are followed.
Which AWS services will help the company assess compliance with these requirements? (Select TWO.)

A. AWS CloudTrail
B. AWS Config
C. AWS Audit Manager
D. Amazon Inspector
E. Amazon CloudWatch

정답：A,B,C

설명：
Comprehensive and Detailed Explanation From Exact AWS AI documents:
To assess compliance, governance, and regulatory adherence throughout the ML application lifecycle, AWS recommends using services that provide audit evidence, configuration tracking, and activity logging.
* AWS Audit Manager continuously evaluates AWS resource usage against predefined regulatory frameworks and internal controls, helping organizations demonstrate compliance.
* AWS Config enables continuous monitoring and recording of AWS resource configurations, allowing organizations to assess whether resources comply with company policies.
* AWS CloudTrail provides a complete audit trail of API calls and user actions, supporting traceability and regulatory investigations.
Together, these services provide end-to-end compliance assessment and monitoring across development and operational phases.
Why the other options are incorrect:
* Amazon Inspector (C) focuses on vulnerability scanning, not governance or regulatory compliance.
* Amazon CloudWatch (D) is primarily used for performance monitoring and logging, not compliance assessment.
AWS AI document references (for exact extracts):
* AWS Governance, Risk, and Compliance (GRC) Overview
* Auditing AI and ML Workloads on AWS
* Security, Compliance, and Monitoring in AWS AI Systems

질문 # 232
A company is using a generative AI model to develop a digital assistant. The model's responses occasionally include undesirable and potentially harmful content. Select the correct Amazon Bedrock filter policy from the following list for each mitigation action. Each filter policy should be selected one time. (Select FOUR.)
* Content filters
* Contextual grounding check
* Denied topics
* Word filters

정답：

설명：

Explanation:
Block input prompts or model responses that contain harmful content such as hate, insults, violence, or misconduct:Content filters Avoid subjects related to illegal investment advice or legal advice:Denied topics Detect and block specific offensive terms:Word filters Detect and filter out information in the model's responses that is not grounded in the provided source information:Contextual grounding check The company is using a generative AI model on Amazon Bedrock and needs to mitigate undesirable and potentially harmful content in the model's responses. Amazon Bedrock provides several guardrail mechanisms, including content filters, denied topics, word filters, and contextual grounding checks, to ensure safe and accurate outputs. Each mitigation action in the hotspot aligns with a specific Bedrock filter policy, and each policy must be used exactly once.
Exact Extract from AWS AI Documents:
From the AWS Bedrock User Guide:
*"Amazon Bedrock guardrails provide mechanisms to control model outputs, including:
Content filters: Block harmful content such as hate speech, violence, or misconduct.
Denied topics: Prevent the model from generating responses on specific subjects, such as illegal activities or advice.
Word filters: Detect and block specific offensive or inappropriate terms.
Contextual grounding check: Ensure responses are grounded in the provided source information, filtering out ungrounded or hallucinated content."*(Source: AWS Bedrock User Guide, Guardrails for Responsible AI) Detailed Explanation:
Block input prompts or model responses that contain harmful content such as hate, insults, violence, or misconduct: Content filtersContent filters in Amazon Bedrock are designed to detect and block harmful content, such as hate speech, insults, violence, or misconduct, ensuring the model's outputs are safe and appropriate. This matches the first mitigation action.
Avoid subjects related to illegal investment advice or legal advice: Denied topicsDenied topics allow users to specify subjects the model should avoid, such as illegal investment advice or legal advice, which could have regulatory implications. This policy aligns with the second mitigation action.
Detect and block specific offensive terms: Word filtersWord filters enable the detection and blocking of specific offensive or inappropriate terms defined by the user, making them ideal for this mitigation action focused on specific terms.
Detect and filter out information in the model's responses that is not grounded in the provided source information: Contextual grounding checkThe contextual grounding check ensures that the model's responses are based on the provided source information, filtering out ungrounded or hallucinated content. This matches the fourth mitigation action.
Hotspot Selection Analysis:
The hotspot lists four mitigation actions, each with the same dropdown options: "Select...," "Content filters,"
"Contextual grounding check," "Denied topics," and "Word filters." The correct selections are:
First action: Content filters
Second action: Denied topics
Third action: Word filters
Fourth action: Contextual grounding check
Each filter policy is used exactly once, as required, and aligns with Amazon Bedrock's guardrail capabilities.
References:
AWS Bedrock User Guide: Guardrails for Responsible AI (https://docs.aws.amazon.com/bedrock/latest
/userguide/guardrails.html)
AWS AI Practitioner Learning Path: Module on Responsible AI and Model Safety Amazon Bedrock Developer Guide: Configuring Guardrails (https://aws.amazon.com/bedrock/)

질문 # 233
A security company is using Amazon Bedrock to run foundation models (FMs). The company wants to ensure that only authorized users invoke the models. The company needs to identify any unauthorized access attempts to set appropriate AWS Identity and Access Management (IAM) policies and roles for future iterations of the FMs.
Which AWS service should the company use to identify unauthorized users that are trying to access Amazon Bedrock?

A. AWS CloudTrail
B. AWS Audit Manager
C. AWS Trusted Advisor
D. Amazon Fraud Detector

정답：A

설명：
AWS CloudTrail is a service that enables governance, compliance, and operational and risk auditing of your AWS account. It tracks API calls and identifies unauthorized access attempts to AWS resources, including Amazon Bedrock.
* AWS CloudTrail:
* Provides detailed logs of all API calls made within an AWS account, including those to Amazon Bedrock.
* Can identify unauthorized access attempts by logging and monitoring the API calls, which helps in setting appropriate IAM policies and roles.
* Why Option B is Correct:
* Monitoring and Security: CloudTrail logs all access requests and helps detect unauthorized access attempts.
* Auditing and Compliance: The logs can be used to audit user activity and enforce security measures.
* Why Other Options are Incorrect:
* A. AWS Audit Manager: Used for automating audit preparation, not for tracking real-time unauthorized access attempts.
* C. Amazon Fraud Detector: Designed to detect fraudulent online activities, not unauthorized access to AWS services.
* D. AWS Trusted Advisor: Provides best practice recommendations for AWS resources, not access monitoring.
Thus, B is the correct answer for identifying unauthorized users attempting to access Amazon Bedrock.

질문 # 234
A company has installed a security camer
a. The company uses an ML model to evaluate the security camera footage for potential thefts. The company has discovered that the model disproportionately flags people who are members of a specific ethnic group.
Which type of bias is affecting the model output?

A. Sampling bias
B. Measurement bias
C. Observer bias
D. Confirmation bias

정답：A

질문 # 235
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