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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q46-Q51):

NEW QUESTION # 46
A company needs to build its own large language model (LLM) based on only the company's private data.
The company is concerned about the environmental effect of the training process.
Which Amazon EC2 instance type has the LEAST environmental effect when training LLMs?

A. Amazon EC2 C series
B. Amazon EC2 G series
C. Amazon EC2 Trn series
D. Amazon EC2 P series

Answer: C

NEW QUESTION # 47
An AI practitioner is using an Amazon Bedrock base model to summarize session chats from the customer service department. The AI practitioner wants to store invocation logs to monitor model input and output data.
Which strategy should the AI practitioner use?

A. Configure model invocation logging in Amazon EventBridge.
B. Configure AWS Audit Manager as the logs destination for the model.
C. Configure AWS CloudTrail as the logs destination for the model.
D. Enable invocation logging in Amazon Bedrock.

Answer: D

NEW QUESTION # 48
A digital devices company wants to predict customer demand for memory hardware. The company does not have coding experience or knowledge of ML algorithms and needs to develop a data-driven predictive model.
The company needs to perform analysis on internal data and external data.
Which solution will meet these requirements?

A. Store the data in Amazon S3. Create ML models and demand forecast predictions by using Amazon SageMaker built-in algorithms that use the data from Amazon S3.
B. Import the data into Amazon SageMaker Canvas. Build ML models and demand forecast predictions by selecting the values in the data from SageMaker Canvas.
C. Import the data into Amazon SageMaker Data Wrangler. Build ML models and demand forecast predictions by using an Amazon Personalize Trending-Now recipe.
D. Import the data into Amazon SageMaker Data Wrangler. Create ML models and demand forecast predictions by using SageMaker built-in algorithms.

Answer: B

Explanation:
I'll continue to format the rest. Let me know if you would like me to provide them all in one go or in parts.

NEW QUESTION # 49
A company has developed an ML model for image classification. The company wants to deploy the model to production so that a web application can use the model.
The company needs to implement a solution to host the model and serve predictions without managing any of the underlying infrastructure.
Which solution will meet these requirements?

A. Use AWS Batch to host the model and serve predictions.
B. Use Amazon SageMaker Serverless Inference to deploy the model.
C. Use Amazon API Gateway to host the model and serve predictions.
D. Use Amazon CloudFront to deploy the model.

Answer: B

NEW QUESTION # 50
A company has built a solution by using generative AI.
The solution uses large language models (LLMs) to translate training manuals from English into other languages.
The company wants to evaluate the accuracy of the solution by examining the text generated for the manuals.
Which model evaluation strategy meets these requirements?

A. Recall-Oriented Understudy for Gisting Evaluation (ROUGE)
B. Bilingual Evaluation Understudy (BLEU)
C. F1 score
D. Root mean squared error (RMSE)

Answer: B

NEW QUESTION # 51
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