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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q69-Q74):

NEW QUESTION # 69
A company is building a customer service chatbot. The company wants the chatbot to improve its responses by learning from past interactions and online resources.
Which AI learning strategy provides this self-improvement capability?

A. Unsupervised learning to find clusters of similar customer inquiries
B. Supervised learning with a continuously updated FAQ database
C. Supervised learning with a manually curated dataset of good responses and bad responses
D. Reinforcement learning with rewards for positive customer feedback

Answer: D

NEW QUESTION # 70
A company is developing a new model to predict the prices of specific items. The model performed well on the training dataset. When the company deployed the model to production, the model's performance decreased significantly.
What should the company do to mitigate this problem?

A. Reduce the volume of data that is used in training.
B. Increase the model training time.
C. Add hyperparameters to the model.
D. Increase the volume of data that is used in training.

Answer: D

NEW QUESTION # 71
A company wants to assess the costs that are associated with using a large language model (LLM) to generate inferences. The company wants to use Amazon Bedrock to build generative AI applications.
Which factor will drive the inference costs?

A. Number of tokens consumed
B. Total training time
C. Temperature value
D. Amount of data used to train the LLM

Answer: A

NEW QUESTION # 72
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. Create ML models and demand forecast predictions by using SageMaker built-in algorithms.
D. Import the data into Amazon SageMaker Data Wrangler. Build ML models and demand forecast predictions by using an Amazon Personalize Trending-Now recipe.

Answer: B

Explanation:
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NEW QUESTION # 73
An AI practitioner has a database of animal photos. The AI practitioner wants to automatically identify and categorize the animals in the photos without manual human effort.
Which strategy meets these requirements?

A. Anomaly detection
B. Named entity recognition
C. Object detection
D. Inpainting

Answer: C

NEW QUESTION # 74
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