aws_1 Flashcards
Pregunta
Respuesta
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to classify the sentiment of text passages as positive or negative.Which prompt engineering strategy meets these requirements?
A.Provide examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified. | B.Provide a detailed explanation of sentiment analysis and how LLMs work in the prompt. | C.Provide the new text passage to be classified without any additional context or examples. | D.Provide the new text passage with a few examples of unrelated tasks, such as text summarization or question answering.
Most Voted Answer: A.Provide examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified.
Answer: A
Justification: Providing examples of text passages with corresponding positive or negative labels helps the model understand the classification task effectively.
Link: https://www.examtopics.com/discussions/amazon/view/150805-exam-aws-certified-ai-practitioner-aif-c01-topic-1-question/
An AI company periodically evaluates its systems and processes with the help of independent software vendors (ISVs). The company needs to receive email message notifications when an ISV’s compliance reports become available.Which AWS service can the company use to meet this requirement?
A.AWS Audit Manager | B.AWS Artifact | C.AWS Trusted Advisor | D.AWS Data Exchange
Most Voted Answer: B.AWS Artifact
Answer: B. AWS Artifact
Justification: AWS Artifact provides on-demand access to AWS compliance reports and allows users to receive notifications when new reports are available.
Link: https://www.examtopics.com/discussions/amazon/view/150807-exam-aws-certified-ai-practitioner-aif-c01-topic-1-question/
A company is using an Amazon Bedrock base model to summarize documents for an internal use case. The company trained a custom model to improve the summarization quality.Which action must the company take to use the custom model through Amazon Bedrock?
A.Purchase Provisioned Throughput for the custom model. | B.Deploy the custom model in an Amazon SageMaker endpoint for real-time inference. | C.Register the model with the Amazon SageMaker Model Registry. | D.Grant access to the custom model in Amazon Bedrock.
Most Voted Answer: A.Purchase Provisioned Throughput for the custom model.
Answer: D. Grant access to the custom model in Amazon Bedrock.
Justification: To use a custom model in Amazon Bedrock, the company must grant access to the model within the Bedrock service.
Link: https://www.examtopics.com/discussions/amazon/view/150829-exam-aws-certified-ai-practitioner-aif-c01-topic-1-question/
A company uses Amazon SageMaker for its ML pipeline in a production environment. The company has large input data sizes up to 1 GB and processing times up to 1 hour. The company needs near real-time latency.Which SageMaker inference option meets these requirements?
A.Real-time inference | B.Serverless inference | C.Asynchronous inference | D.Batch transform
Most Voted Answer: C.Asynchronous inference
Answer: A. Real-time inference
Justification: Real-time inference provides low-latency predictions suitable for near real-time applications, which is necessary given the company’s requirements.
Link: https://www.examtopics.com/discussions/amazon/view/150626-exam-aws-certified-ai-practitioner-aif-c01-topic-1-question/
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.
Most Voted Answer: A.Create an Amazon Bedrock custom service role for each team that has access to only the team’s customer data.
Answer: D
Justification: This solution allows for controlled access to customer data by creating IAM roles for each team that restrict access to their specific customer folders in S3, while using a single Bedrock role for model access.
Link: https://www.examtopics.com/discussions/amazon/view/151076-exam-aws-certified-ai-practitioner-aif-c01-topic-1-question/
Which AWS service or feature can help an AI development team quickly deploy and consume a foundation model (FM) within the team’s VPC?
A.Amazon Personalize | B.Amazon SageMaker JumpStart | C.PartyRock, an Amazon Bedrock Playground | D.Amazon SageMaker endpoints
Most Voted Answer: B.Amazon SageMaker JumpStart
Answer: B. Amazon SageMaker JumpStart
Justification: Amazon SageMaker JumpStart provides pre-built solutions and models, including foundation models, that can be quickly deployed within a team’s VPC.
Link: https://www.examtopics.com/discussions/amazon/view/150812-exam-aws-certified-ai-practitioner-aif-c01-topic-1-question/
A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents.Which solution meets these requirements?
A.Build an automatic named entity recognition system. | B.Create a recommendation engine. | C.Develop a summarization chatbot. | D.Develop a multi-language translation system.
Most Voted Answer: C.Develop a summarization chatbot.
Answer: C
Justification: A summarization chatbot can effectively read legal documents and extract key points, aligning with the law firm’s requirement to summarize content.
Link: https://www.examtopics.com/discussions/amazon/view/150664-exam-aws-certified-ai-practitioner-aif-c01-topic-1-question/
