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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q49-Q54):

NEW QUESTION # 49
A company is using few-shot prompting on a base model that is hosted on Amazon Bedrock. The model currently uses 10 examples in the prompt. The model is invoked once daily and is performing well. The company wants to lower the monthly cost.
Which solution will meet these requirements?

A. Increase the number of tokens in the prompt.
B. Customize the model by using fine-tuning.
C. Use Provisioned Throughput.
D. Decrease the number of tokens in the prompt.

Answer: D

NEW QUESTION # 50
A company is building a solution to generate images for protective eyewear. The solution must have high accuracy and must minimize the risk of incorrect annotations.
Which solution will meet these requirements?

A. Data summarization by using Amazon QuickSight
B. Data augmentation by using an Amazon Bedrock knowledge base
C. Image recognition by using Amazon Rekognition
D. Human-in-the-loop validation by using Amazon SageMaker Ground Truth Plus

Answer: D

NEW QUESTION # 51
A company is building a chatbot to improve user experience. The company is using a large language model (LLM) from Amazon Bedrock for intent detection. The company wants to use few-shot learning to improve intent detection accuracy.
Which additional data does the company need to meet these requirements?

A. Pairs of user intents and correct chatbot responses
B. Pairs of user messages and correct user intents
C. Pairs of user messages and correct chatbot responses
D. Pairs of chatbot responses and correct user intents

Answer: B

NEW QUESTION # 52
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to know how much information can fit into one prompt.
Which consideration will inform the company's decision?

A. Temperature
B. Model size
C. Batch size
D. Context window

Answer: D

NEW QUESTION # 53
What are tokens in the context of generative AI models?

A. Tokens are the basic units of input and output that a generative AI model operates on, representing words, subwords, or other linguistic units.
B. Tokens are the mathematical representations of words or concepts used in generative AI models.
C. Tokens are the pre-trained weights of a generative AI model that are fine-tuned for specific tasks.
D. Tokens are the specific prompts or instructions given to a generative AI model to generate output.

Answer: A

NEW QUESTION # 54
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