Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification tasks?
Correct Answer:
B
Measuring the model's accuracy against a predefined benchmark dataset is the correct strategy to evaluate the accuracy of a foundation model (FM) used in image classification tasks.
✑ Model Accuracy Evaluation:
✑ Why Option B is Correct:
✑ Why Other Options are Incorrect:
How can companies use large language models (LLMs) securely on Amazon Bedrock?
Correct Answer:
A
To securely use large language models (LLMs) on Amazon Bedrock, companies should design clear and specific prompts to avoid unintended outputs and ensure proper configuration of AWS Identity and Access Management (IAM) roles and policies with the principle of least privilege. This approach limits access to sensitive resources and minimizes the potential impact of security incidents.
✑ Option A (Correct): "Design clear and specific prompts. Configure AWS Identity
and Access Management (IAM) roles and policies by using least privilege access": This is the correct answer as it directly addresses both security practices in prompt design and access management.
✑ Option B: "Enable AWS Audit Manager for automatic model evaluation jobs" is
incorrect because Audit Manager is for compliance and auditing, not directly related to secure LLM usage.
✑ Option C: "Enable Amazon Bedrock automatic model evaluation jobs" is incorrect
because Bedrock does not provide automatic model evaluation jobs specifically for security purposes.
✑ Option D: "Use Amazon CloudWatch Logs to make models explainable and to
monitor for bias" is incorrect because CloudWatch Logs are used for monitoring and not directly for making models explainable or secure.
AWS AI Practitioner References:
✑ Secure AI Practices on AWS: AWS recommends configuring IAM roles and using least privilege access to ensure secure usage of AI models.
Which option is a benefit of using Amazon SageMaker Model Cards to document AI models?
Correct Answer:
B
Amazon SageMaker Model Cards provide a standardized way to document important details about an AI model, such as its purpose, performance, intended usage, and known limitations. This enables transparency and compliance while fostering better communication between stakeholders. It does not store models physically or optimize computational requirements. References: AWS SageMaker Model Cards Documentation.
A company wants to develop an educational game where users answer questions such as the following: "A jar contains six red, four green, and three yellow marbles. What is the probability of choosing a green marble from the jar?"
Which solution meets these requirements with the LEAST operational overhead?
Correct Answer:
C
The problem involves a simple probability calculation that can be handled efficiently by straightforward mathematical rules and computations. Using machine learning techniques would introduce unnecessary complexity and operational overhead.
✑ Option C (Correct): "Use code that will calculate probability by using simple rules and computations": This is the correct answer because it directly solves the problem with minimal overhead, using basic probability rules.
✑ Option A: "Use supervised learning to create a regression model" is incorrect as it overcomplicates the solution for a simple probability problem.
✑ Option B: "Use reinforcement learning to train a model" is incorrect because reinforcement learning is not needed for a simple probability calculation.
✑ Option D: "Use unsupervised learning to create a model" is incorrect as unsupervised learning is not applicable to this task.
AWS AI Practitioner References:
✑ Choosing the Right Solution for AI Tasks: AWS recommends using the simplest and most efficient approach to solve a given problem, avoiding unnecessary machine learning techniques for straightforward tasks.
A financial institution is using Amazon Bedrock to develop an AI application. The application is hosted in a VPC. To meet regulatory compliance standards, the VPC is not allowed access to any internet traffic.
Which AWS service or feature will meet these requirements?
Correct Answer:
A
AWS PrivateLink enables private connectivity between VPCs and AWS services without exposing traffic to the public internet. This feature is critical for meeting regulatory compliance standards that require isolation from public internet traffic.
✑ Option A (Correct): "AWS PrivateLink": This is the correct answer because it
allows secure access to Amazon Bedrock and other AWS services from a VPC without internet access, ensuring compliance with regulatory standards.
✑ Option B: "Amazon Macie" is incorrect because it is a security service for data
classification and protection, not for managing private network traffic.
✑ Option C: "Amazon CloudFront" is incorrect because it is a content delivery network service and does not provide private network connectivity.
✑ Option D: "Internet gateway" is incorrect as it enables internet access, which violates the VPC's no-internet-traffic policy.
AWS AI Practitioner References:
✑ AWS PrivateLink Documentation: AWS highlights PrivateLink as a solution for connecting VPCs to AWS services privately, which is essential for organizations
with strict regulatory requirements.
