AIF-C01 practice questions 161–170

1. Question 161 · 417 in bank

   Which scenario describes a potential risk and limitation of prompt engineering in the context of a generative AI model?

   • APrompt engineering does not ensure that the model always produces consistent and deterministic outputs, eliminating the need for validation.
   • BPrompt engineering could expose the model to vulnerabilities such as prompt injection attacks.
   • CProperly designed prompts reduce but do not eliminate the risk of data poisoning or model hijacking.
   • DPrompt engineering does not ensure that the model will consistently generate highly reliable outputs when working with real-world data.

   Show answer

   Answer: B

   Next question

2. Question 162 · 417 in bank

   A publishing company built a Retrieval Augmented Generation (RAG) based solution to give its users the ability to interact with published content. New content is published daily. The company wants to provide a near real-time experience to users. Which steps in the RAG pipeline should the company implement by using offline batch processing to meet these requirements? (Choose two.)

   • AGeneration of content embeddings
   • BGeneration of embeddings for user queries
   • CCreation of the search index
   • DRetrieval of relevant content
   • EResponse generation for the user

   Show answer

   Answer: A

   Next question

3. Question 163 · 417 in bank

   Which technique breaks a complex task into smaller subtasks that are sent sequentially to a large language model (LLM)?

   • AOne-shot prompting
   • BPrompt chaining
   • CTree of thoughts
   • DRetrieval Augmented Generation (RAG)

   Show answer

   Answer: B

   Next question

4. Question 164 · 417 in bank

   An AI practitioner needs to improve the accuracy of a natural language generation model. The model uses rapidly changing inventory data. Which technique will improve the model's accuracy?

   • ATransfer learning
   • BFederated learning
   • CRetrieval Augmented Generation (RAG)
   • DOne-shot prompting

   Show answer

   Answer: C

   Next question

5. Question 165 · 417 in bank

   A company wants to collaborate with several research institutes to develop an AI model. The company needs standardized documentation of model version tracking and a record of model development. Which solution meets these requirements?

   • ATrack the model changes by using Git.
   • BTrack the model changes by using Amazon Fraud Detector.
   • CTrack the model changes by using Amazon SageMaker Model Cards.
   • DTrack the model changes by using Amazon Comprehend.

   Show answer

   Answer: C

   Next question

6. Question 166 · 417 in bank

   A company that uses multiple ML models wants to identify changes in original model quality so that the company can resolve any issues. Which AWS service or feature meets these requirements?

   • AAmazon SageMaker JumpStart
   • BAmazon SageMaker HyperPod
   • CAmazon SageMaker Data Wrangler
   • DAmazon SageMaker Model Monitor

   Show answer

   Answer: D

   Next question

7. Question 167 · 417 in bank

   What is the purpose of chunking in Retrieval Augmented Generation (RAG)?

   • ATo avoid database storage limitations for large text documents by storing parts or chunks of the text
   • BTo improve efficiency by avoiding the need to convert large text into vector embeddings
   • CTo improve the contextual relevancy of results retrieved from the vector index
   • DTo decrease the cost of storage by storing parts or chunks of the text

   Show answer

   Answer: C

   Next question

8. Question 168 · 417 in bank

   A company is developing an editorial assistant application that uses generative AI. During the pilot phase, usage is low and application performance is not a concern. The company cannot predict application usage after the application is fully deployed and wants to minimize application costs. Which solution will meet these requirements?

   • AUse GPU-powered Amazon EC2 instances.
   • BUse Amazon Bedrock with Provisioned Throughput.
   • CUse Amazon Bedrock with On-Demand Throughput.
   • DUse Amazon SageMaker JumpStart.

   Show answer

   Answer: C

   Next question

9. Question 169 · 417 in bank

   A company deployed a Retrieval Augmented Generation (RAG) application on Amazon Bedrock that gathers financial news to distribute in daily newsletters. Users have recently reported politically influenced ideas in the newsletters. Which Amazon Bedrock guardrail can identify and filter this content?

   • AWord filters
   • BDenied topics
   • CSensitive information filters
   • DContent filters

   Show answer

   Answer: B

   Next question

10. Question 170 · 417 in bank

    A financial company is developing a fraud detection system that flags potential fraud cases in credit card transactions. Employees will evaluate the flagged fraud cases. The company wants to minimize the amount of time the employees spend reviewing flagged fraud cases that are not actually fraudulent. Which evaluation metric meets these requirements?

    • ARecall
    • BAccuracy
    • CPrecision
    • DLift chart

    Show answer

    Answer: C

    Next question

Keyboard:J Kmove between questionsA–Dselect an answerRshow or hide the answer← →change page

AIF-C01 practice, question 161. 417 questions available.