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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q54-Q59):

NEW QUESTION # 54
A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions.
Which business objective should the company use to evaluate the effect of the LLM chatbot?

A. Average call duration
B. Corporate social responsibility
C. Regulatory compliance
D. Website engagement rate

Answer: A

NEW QUESTION # 55
A company is building an ML model to analyze archived data. The company must perform inference on large datasets that are multiple GBs in size. The company does not need to access the model predictions immediately.
Which Amazon SageMaker inference option will meet these requirements?

A. Batch transform
B. Real-time inference
C. Asynchronous inference
D. Serverless inference

Answer: A

Explanation:
I'll continue with more questions shortly. Stay tuned!

NEW QUESTION # 56
A company is using the Generative AI Security Scoping Matrix to assess security responsibilities for its solutions. The company has identified four different solution scopes based on the matrix.
Which solution scope gives the company the MOST ownership of security responsibilities?

A. Building and training a generative AI model from scratch by using specific data that a customer owns.
B. Building an application by using an existing third-party generative AI foundation model (FM).
C. Refining an existing third-party generative AI foundation model (FM) by fine-tuning the model by using data specific to the business.
D. Using a third-party enterprise application that has embedded generative AI features.

Answer: A

NEW QUESTION # 57
A company wants to use generative AI to increase developer productivity and software development. The company wants to use Amazon Q Developer.
What can Amazon Q Developer do to help the company meet these requirements?

A. Run an application without provisioning or managing servers.
B. Enable voice commands for coding and providing natural language search.
C. Create software snippets, reference tracking, and open-source license tracking.
D. Convert audio files to text documents by using ML models.

Answer: B

NEW QUESTION # 58
An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate inference responses based on confidential data.
How should the AI practitioner prevent responses based on confidential data?

A. Encrypt the confidential data in the inference responses by using Amazon SageMaker.
B. Delete the custom model. Remove the confidential data from the training dataset. Retrain the custom model.
C. Mask the confidential data in the inference responses by using dynamic data masking.
D. Encrypt the confidential data in the custom model by using AWS Key Management Service (AWS KMS).

Answer: B

NEW QUESTION # 59
......

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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q54-Q59):

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