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.
A company needs to build its own large language model (LLM) based on only the company's private data. The company is concerned about the environmental effect of the training process.
Which Amazon EC2 instance type has the LEAST environmental effect when training LLMs?
Correct Answer:
D
The Amazon EC2 Trn series (Trainium) instances are designed for high-performance, cost- effective machine learning training while being energy-efficient. AWS Trainium-powered instances are optimized for deep learning models and have been developed to minimize environmental impact by maximizing energy efficiency.
✑ Option D (Correct): "Amazon EC2 Trn series": This is the correct answer because the Trn series is purpose-built for training deep learning models with lower energy consumption, which aligns with the company's concern about environmental effects.
✑ Option A: "Amazon EC2 C series" is incorrect because it is intended for compute-
intensive tasks but not specifically optimized for ML training with environmental considerations.
✑ Option B: "Amazon EC2 G series" (Graphics Processing Unit instances) is
optimized for graphics-intensive applications but does not focus on minimizing environmental impact for training.
✑ Option C: "Amazon EC2 P series" is designed for ML training but does not offer
the same level of energy efficiency as the Trn series.
AWS AI Practitioner References:
✑ AWS Trainium Overview: AWS promotes Trainium instances as their most energy- efficient and cost-effective solution for ML model training.
Which option is a use case for generative AI models?
Correct Answer:
B
Generative AI models are used to create new content based on existing data. One common use case is generating photorealistic images from text descriptions, which is particularly useful in digital marketing, where visual content is key to engaging potential customers.
✑ Option B (Correct): "Creating photorealistic images from text descriptions for digital
marketing": This is the correct answer because generative AI models, like those offered by Amazon Bedrock, can create images based on text descriptions, making them highly valuable for generating marketing materials.
✑ Option A: "Improving network security by using intrusion detection systems" is
incorrect because this is a use case for traditional machine learning models, not generative AI.
✑ Option C: "Enhancing database performance by using optimized indexing" is
incorrect as it is unrelated to generative AI.
✑ Option D: "Analyzing financial data to forecast stock market trends" is incorrect because it typically involves predictive modeling rather than generative AI.
AWS AI Practitioner References:
✑ Use Cases for Generative AI Models on AWS: AWS highlights the use of generative AI for creative content generation, including image creation, text generation, and more, which is suited for digital marketing applications.
A company wants to build an ML model by using Amazon SageMaker. The company needs to share and manage variables for model development across multiple teams.
Which SageMaker feature meets these requirements?
Correct Answer:
A
Amazon SageMaker Feature Store is the correct solution for sharing and managing variables (features) across multiple teams during model development.
✑ Amazon SageMaker Feature Store:
✑ Why Option A is Correct:
✑ Why Other Options are Incorrect:
A company is training a foundation model (FM). The company wants to increase the accuracy of the model up to a specific acceptance level.
Which solution will meet these requirements?
Correct Answer:
B
Increasing the number of epochs during model training allows the model to learn from the data over more iterations, potentially improving its accuracy up to a certain point. This is a common practice when attempting to reach a specific level of accuracy.
✑ Option B (Correct): "Increase the epochs": This is the correct answer because
increasing epochs allows the model to learn more from the data, which can lead to higher accuracy.
✑ Option A: "Decrease the batch size" is incorrect as it mainly affects training speed
and may lead to overfitting but does not directly relate to achieving a specific accuracy level.
✑ Option C: "Decrease the epochs" is incorrect as it would reduce the training time,
possibly preventing the model from reaching the desired accuracy.
✑ Option D: "Increase the temperature parameter" is incorrect because temperature affects the randomness of predictions, not model accuracy.
AWS AI Practitioner References:
✑ Model Training Best Practices on AWS: AWS suggests adjusting training parameters, like the number of epochs, to improve model performance.