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Amazon AIF-C01 Practice Test - Questions Answers, Page 5

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Question 41

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A company has a foundation model (FM) that was customized by using Amazon Bedrock to answer customer queries about products. The company wants to validate the model's responses to new types of queries. The company needs to upload a new dataset that Amazon Bedrock can use for validation.

Which AWS service meets these requirements?

Amazon S3
Amazon S3
Amazon Elastic Block Store (Amazon EBS)
Amazon Elastic Block Store (Amazon EBS)
Amazon Elastic File System (Amazon EFS)
Amazon Elastic File System (Amazon EFS)
AWS Snowcone
AWS Snowcone
Suggested answer: A
asked 16/09/2024
Tym Dom
41 questions

Question 42

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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?

Number of tokens consumed
Number of tokens consumed
Temperature value
Temperature value
Amount of data used to train the LLM
Amount of data used to train the LLM
Total training time
Total training time
Suggested answer: A
asked 16/09/2024
Elizabeth Holland
41 questions

Question 43

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An AI company periodically evaluates its systems and processes with the help of independent software vendors (ISVs). The company needs to receive email message notifications when an ISV's compliance reports become available.

Which AWS service can the company use to meet this requirement?

AWS Audit Manager
AWS Audit Manager
AWS Artifact
AWS Artifact
AWS Trusted Advisor
AWS Trusted Advisor
AWS Data Exchange
AWS Data Exchange
Suggested answer: B
asked 16/09/2024
FUKUMOTO AYUMI
31 questions

Question 44

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A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company needs the LLM to produce more consistent responses to the same input prompt.

Which adjustment to an inference parameter should the company make to meet these requirements?

Decrease the temperature value
Decrease the temperature value
Increase the temperature value
Increase the temperature value
Decrease the length of output tokens
Decrease the length of output tokens
Increase the maximum generation length
Increase the maximum generation length
Suggested answer: A
asked 16/09/2024
André Batista
39 questions

Question 45

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A company is implementing the Amazon Titan foundation model (FM) by using Amazon Bedrock. The company needs to supplement the model by using relevant data from the company's private data sources.

Which solution will meet this requirement?

Use a different FM
Use a different FM
Choose a lower temperature value
Choose a lower temperature value
Create an Amazon Bedrock knowledge base
Create an Amazon Bedrock knowledge base
Enable model invocation logging
Enable model invocation logging
Suggested answer: C
asked 16/09/2024
Jenny Silva
42 questions

Question 46

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A company wants to develop an educational game where users answer questions such as the following: 'A jar contains six red, four green, and three yellow marbles. What is the probability of choosing a green marble from the jar?'

Which solution meets these requirements with the LEAST operational overhead?

Use supervised learning to create a regression model that will predict probability.
Use supervised learning to create a regression model that will predict probability.
Use reinforcement learning to train a model to return the probability.
Use reinforcement learning to train a model to return the probability.
Use code that will calculate probability by using simple rules and computations.
Use code that will calculate probability by using simple rules and computations.
Use unsupervised learning to create a model that will estimate probability density.
Use unsupervised learning to create a model that will estimate probability density.
Suggested answer: C
asked 16/09/2024
Rudy Raijmakers
40 questions

Question 47

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Which functionality does Amazon SageMaker Clarify provide?

Integrates a Retrieval Augmented Generation (RAG) workflow
Integrates a Retrieval Augmented Generation (RAG) workflow
Monitors the quality of ML models in production
Monitors the quality of ML models in production
Documents critical details about ML models
Documents critical details about ML models
Identifies potential bias during data preparation
Identifies potential bias during data preparation
Suggested answer: D
asked 16/09/2024
Ahsan Ilyas
32 questions

Question 48

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A company is building an ML model. The company collected new data and analyzed the data by creating a correlation matrix, calculating statistics, and visualizing the data.

Which stage of the ML pipeline is the company currently in?

Data pre-processing
Data pre-processing
Feature engineering
Feature engineering
Exploratory data analysis
Exploratory data analysis
Hyperparameter tuning
Hyperparameter tuning
Suggested answer: C
asked 16/09/2024
Kayode Omotosho
40 questions

Question 49

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A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text.

Which type of model meets this requirement?

Topic modeling
Topic modeling
Clustering models
Clustering models
Prescriptive ML models
Prescriptive ML models
BERT-based models
BERT-based models
Suggested answer: D
asked 16/09/2024
Armands Vestmanis
45 questions

Question 50

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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?

Pairs of chatbot responses and correct user intents
Pairs of chatbot responses and correct user intents
Pairs of user messages and correct chatbot responses
Pairs of user messages and correct chatbot responses
Pairs of user messages and correct user intents
Pairs of user messages and correct user intents
Pairs of user intents and correct chatbot responses
Pairs of user intents and correct chatbot responses
Suggested answer: C
asked 16/09/2024
Chet Camlin
33 questions
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Related questions

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?
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