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AIF-C01 Practice Questions

AWS Certified AI Practitioner Exam

Last Update 3 days ago
Total Questions : 371

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Question # 61

A company wants to implement a generative AI assistant to provide consistent responses to various phrasings of user questions.

Which advantages can generative AI provide in this use case?

Options:

A.  

Low latency and high throughput

B.  

Adaptability and responsiveness

C.  

Deterministic outputs and fixed responses

D.  

Hardware acceleration and GPU optimization

Discussion 0
Question # 62

A company wants to use an AI model to generate labels for online news articles that the company publishes. The company selects a foundation model (FM) instead of a conventional ML model for this task.

What is one advantage of using an FM instead of a conventional ML model to meet this requirement?

Options:

A.  

An FM does not require training.

B.  

An FM is smaller and faster.

C.  

An FM is more transparent.

D.  

An FM is not biased.

Discussion 0
Question # 63

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?

Options:

A.  

Track the model changes by using Git.

B.  

Track the model changes by using Amazon Fraud Detector.

C.  

Track the model changes by using Amazon SageMaker Model Cards.

D.  

Track the model changes by using Amazon Comprehend.

Discussion 0
Question # 64

Which term is an example of output vulnerability?

Options:

A.  

Model misuse

B.  

Data poisoning

C.  

Data leakage

D.  

Parameter stealing

Discussion 0
Question # 65

A company wants to use AI to protect its application from threats. The AI solution needs to check if an IP address is from a suspicious source.

Options:

A.  

Build a speech recognition system

B.  

Create a natural language processing (NLP) named entity recognition system

C.  

Develop an anomaly detection system

D.  

Create a fraud forecasting system

Discussion 0
Question # 66

A financial institution is using Amazon Bedrock to develop an AI application. The application is hosted in a VP

C.  

To meet regulatory compliance standards, the VPC is not allowed access to any internet traffic.

Which AWS service or feature will meet these requirements?

Options:

A.  

AWS PrivateLink

B.  

Amazon Macie

C.  

Amazon CloudFront

D.  

Internet gateway

Discussion 0
Question # 67

A social media company wants to use a large language model (LLM) to summarize messages. The company has chosen a few LLMs that are available on Amazon SageMaker JumpStart. The company wants to compare the generated output toxicity of these models.

Which strategy gives the company the ability to evaluate the LLMs with the LEAST operational overhead?

Options:

A.  

Crowd-sourced evaluation

B.  

Automatic model evaluation

C.  

Model evaluation with human workers

D.  

Reinforcement learning from human feedback (RLHF)

Discussion 0
Question # 68

A hospital is developing an AI system to assist doctors in diagnosing diseases based on patient records and medical images. To comply with regulations, the sensitive patient data must not leave the country the data is located in.

Which data governance strategy will ensure compliance and protect patient privacy?

Options:

A.  

Data residency

B.  

Data quality

C.  

Data discoverability

D.  

Data enrichment

Discussion 0
Question # 69

A company is developing an ML model to support the company ' s retail application. The company wants to use information that the model has produced from previous tasks to increase the learning speed of the model.

Which model training solution will meet these requirements?

Options:

A.  

Supervised learning

B.  

Hyperparameter tuning

C.  

Regularization techniques

D.  

Transfer learning

Discussion 0
Question # 70

A company wants to fine-tune a foundation model (FM) for a specific use case. The company needs to deploy the FM on Amazon Bedrock for internal use.

Which solution will meet these requirements?

Options:

A.  

Run responses that have been generated by a pre-trained FM through Amazon Bedrock Guardrails to create the custom FM.

B.  

Use Amazon Personalize to customize the FM with custom data.

C.  

Use conversational builder for Amazon Bedrock Agents to create the custom model.

D.  

Use Amazon SageMaker AI to customize the FM. Then, import the trained model into Amazon Bedrock.

Discussion 0
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