31. A company wants to develop a large language model (LLM) application by using Amazon Bedrock and customer data that is uploaded to Amazon S3. The company’s security policy states that each team can access data for only the team’s own customers.
Which solution will meet these requirements?
A. Create an Amazon Bedrock custom service role for each team that has access to only the team’s customer data.
B. Create a custom service role that has Amazon S3 access. Ask teams to specify the customer name on each Amazon Bedrock request.
C. Redact personal data in Amazon S3. Update the S3 bucket policy to allow team access to customer data.
D. Create one Amazon Bedrock role that has full Amazon S3 access. Create IAM roles for each team that have access to only each team’s customer folders.
Answer
A
32. A medical company deployed a disease detection model on Amazon Bedrock. To comply with privacy policies, the company wants to prevent the model from including personal patient information in its responses. The company also wants to receive notification when policy violations occur.
Which solution meets these requirements?
A. Use Amazon Macie to scan the model’s output for sensitive data and set up alerts for potential violations.
B. Configure AWS CloudTrail to monitor the model’s responses and create alerts for any detected personal information.
C. Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms for notification of policy violations.
D. Implement Amazon SageMaker Model Monitor to detect data drift and receive alerts when model quality degrades.
Answer
C
33. An education provider is building a question and answer application that uses a generative AI model to explain complex concepts. The education provider wants to automatically change the style of the model response depending on who is asking the question. The education provider will give the model the age range of the user who has asked the question.
Which solution meets these requirements with the LEAST implementation effort?
A. Fine-tune the model by using additional training data that is representative of the various age ranges that the application will support.
B. Add a role description to the prompt context that instructs the model of the age range that the response should target.
C. Use chain-of-thought reasoning to deduce the correct style and complexity for a response suitable for that user.
D. Summarize the response text depending on the age of the user so that younger users receive shorter responses.
Answer
B
34. Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification tasks?
A. Calculate the total cost of resources used by the model.
B. Measure the model’s accuracy against a predefined benchmark dataset.
C. Count the number of layers in the neural network.
D. Assess the color accuracy of images processed by the model.
Answer
B
35. An accounting firm wants to implement a large language model (LLM) to automate document processing. The firm must proceed responsibly to avoid potential harms.
What should the firm do when developing and deploying the LLM? (Choose two.)
A. Include fairness metrics for model evaluation.
B. Adjust the temperature parameter of the model.
C. Modify the training data to mitigate bias.
D. Avoid overfitting on the training data.
E. Apply prompt engineering techniques.
Answer
A, C
36. A company is building an ML model. The company collected new data and analyzed the data by creating a correlation matrix, calculating statistics, and visualizing the data.
Which stage of the ML pipeline is the company currently in?
A. Data pre-processing
B. Feature engineering
C. Exploratory data analysis
D. Hyperparameter tuning
Answer
C
37. A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text.
Which type of model meets this requirement?
A. Topic modeling
B. Clustering models
C. Prescriptive ML models
D. BERT-based models
Answer
D
38. A company wants to display the total sales for its top-selling products across various retail locations in the past 12 months.
Which AWS solution should the company use to automate the generation of graphs?
A. Amazon Q in Amazon EC2
B. Amazon Q Developer
C. Amazon Q in Amazon QuickSight
D. Amazon Q in AWS Chatbot
Answer
C
39. A company is building a chatbot to improve user experience. The company is using a large language model (LLM) from Amazon Bedrock for intent detection. The company wants to use few-shot learning to improve intent detection accuracy.
Which additional data does the company need to meet these requirements?
A. Pairs of chatbot responses and correct user intents
B. Pairs of user messages and correct chatbot responses
C. Pairs of user messages and correct user intents
D. Pairs of user intents and correct chatbot responses
Answer
C
40. A company is using few-shot prompting on a base model that is hosted on Amazon Bedrock. The model currently uses 10 examples in the prompt. The model is invoked once daily and is performing well. The company wants to lower the monthly cost.
Which solution will meet these requirements?
A. Customize the model by using fine-tuning.
B. Decrease the number of tokens in the prompt.
C. Increase the number of tokens in the prompt.
D. Use Provisioned Throughput.
Answer
B