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AIF-C01 Exam Dumps - AWS Certified AI Practitioner Exam

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Question # 17

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.

Context window

C.

Batch size

D.

Model size

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Question # 18

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 AWS CloudTrail as the logs destination for the model.

B.

Enable invocation logging in Amazon Bedrock.

C.

Configure AWS Audit Manager as the logs destination for the model.

D.

Configure model invocation logging in Amazon EventBridge.

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Question # 19

A company has petabytes of unlabeled customer data to use for an advertisement campaign. The company wants to classify its customers into tiers to advertise and promote the company's products.

Which methodology should the company use to meet these requirements?

A.

Supervised learning

B.

Unsupervised learning

C.

Reinforcement learning

D.

Reinforcement learning from human feedback (RLHF)

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Question # 20

A pharmaceutical company wants to analyze user reviews of new medications and provide a concise overview for each medication. Which solution meets these requirements?

A.

Create a time-series forecasting model to analyze the medication reviews by using Amazon Personalize.

B.

Create medication review summaries by using Amazon Bedrock large language models (LLMs).

C.

Create a classification model that categorizes medications into different groups by using Amazon SageMaker.

D.

Create medication review summaries by using Amazon Rekognition.

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Question # 21

A company is building a contact center application and wants to gain insights from customer conversations. The company wants to analyze and extract key information from the audio of the customer calls.

Which solution meets these requirements?

A.

Build a conversational chatbot by using Amazon Lex.

B.

Transcribe call recordings by using Amazon Transcribe.

C.

Extract information from call recordings by using Amazon SageMaker Model Monitor.

D.

Create classification labels by using Amazon Comprehend.

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Question # 22

A company wants to use language models to create an application for inference on edge devices. The inference must have the lowest latency possible.

Which solution will meet these requirements?

A.

Deploy optimized small language models (SLMs) on edge devices.

B.

Deploy optimized large language models (LLMs) on edge devices.

C.

Incorporate a centralized small language model (SLM) API for asynchronous communication with edge devices.

D.

Incorporate a centralized large language model (LLM) API for asynchronous communication with edge devices.

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Question # 23

A company wants to classify human genes into 20 categories based on gene characteristics. The company needs an ML algorithm to document how the inner mechanism of the model affects the output.

Which ML algorithm meets these requirements?

A.

Decision trees

B.

Linear regression

C.

Logistic regression

D.

Neural networks

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Question # 24

Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification tasks?

A.

Calculate the total cost of resources used by the model.

B.

Measure the model's accuracy against a predefined benchmark dataset.

C.

Count the number of layers in the neural network.

D.

Assess the color accuracy of images processed by the model.

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