Question 1

How does the inference parameter Response length influence the model response for Amazon Bedrock?

Options :

A : Specifies the sequences of characters that stop the model from generating further tokens

B : Influences the percentage of most-likely candidates that the model considers for the next token

C : Specifies the minimum or maximum number of tokens to return in the generated response.

D : Influences the number of most-likely candidates that the model considers for the next token

Answer: C

Question 2

A healthcare analytics company aims to enhance its AI capabilities by fine-tuning a foundation model (FM) in Amazon Bedrock to specialize in medical text analysis. To achieve this, the company plans to use its own task-specific labeled dataset, consisting of annotated clinical notes and medical records, to fine-tune the model for greater accuracy in extracting relevant information.Given these requirements, which approach would be most suitable?

Options :

A : The company should use On-Demand mode, which provides flexibility by charging only for the resources consumed

B : The company should leverage Amazon Bedrock playground to facilitate fine-tuning of the model

C : The company should leverage batch inference to facilitate fine-tuning of the model

D : The company should use Provisioned Throughput mode, which allows the company to reserve a specific amount of capacity in advanc

Answer: D

Question 3

What is a key difference between Amazon Bedrock and Amazon SageMaker JumpStart?

Options :

A : Amazon Bedrock provides foundational models for generative AI applications, whereas Amazon SageMaker JumpStart offers pre-built solutions and one-click deployment for various machine learning models

B : Amazon SageMaker JumpStart provides foundational models for generative AI applications, whereas Amazon Bedrock offers pre-built solutions and one-click deployment for various machine learning models

C : Amazon SageMaker JumpStart is designed for building and scaling machine learning models, whereas Amazon Bedrock is used for real-time data analytics

D : Amazon Bedrock is designed for building and scaling machine learning models, whereas Amazon SageMaker JumpStart is used for real-time data analytics

Answer: A

Question 4

A company is testing the security of a foundation model (FM). During testing, the company wants to get around the safety features and make harmful content.

Options :

A : Fuzzing training data to find vulnerabilities

B : Denial of service (DoS)

C : Penetration testing with authorization

D : Jailbreak

Answer: D

Question 5

Which AWS service offers pre-trained and customizable computer vision (CV) capabilities?

Options :

A : Amazon Rekognition

B : Amazon SageMaker

C : Amazon DeepRacer

D : Amazon Textract

Answer: A

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