A company has built an image classification model to predict plant diseases from photos of plant leaves. The company wants to evaluate how many images the model classified correctly.

Which evaluation metric should the company use to measure the model's performance?

A. R-squared score

B. Accuracy

C. Root mean squared error (RMSE)

D. Learning rate

An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate inference responses based on confidential data.

How should the AI practitioner prevent responses based on confidential data?

A. Delete the custom model. Remove the confidential data from the training dataset. Retrain the custom model.

B. Mask the confidential data in the inference responses by using dynamic data masking.

C. Encrypt the confidential data in the inference responses by using Amazon SageMaker.

D. Encrypt the confidential data in the custom model by using AWS Key Management Service (AWS KMS).

A company needs to build its own large language model (LLM) based on only the company's private data. The company is concerned about the environmental effect of the training process.

Which Amazon EC2 instance type has the LEAST environmental effect when training LLMs?

A. Amazon EC2 C series

B. Amazon EC2 G series

C. Amazon EC2 P series

D. Amazon EC2 Trn series

A company wants to use a large language model (LLM) to develop a conversational agent. The company needs to prevent the LLM from being manipulated with common prompt engineering techniques to perform undesirable actions or expose sensitive information.

Which action will reduce these risks?

A. Create a prompt template that teaches the LLM to detect attack patterns.

B. Increase the temperature parameter on invocation requests to the LLM.

C. Avoid using LLMs that are not listed in Amazon SageMaker.

D. Decrease the number of input tokens on invocations of the LLM.

A company built a deep learning model for object detection and deployed the model to production.
Which AI process occurs when the model analyzes a new image to identify objects?

A. Training

B. Inference

C. Model deployment

D. Bias correction

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.

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.

A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents.

Which solution meets these requirements?

A. Build an automatic named entity recognition system.

B. Create a recommendation engine.

C. Develop a summarization chatbot.

D. Develop a multi-language translation system.

An AI practitioner wants to use a foundation model (FM) to design a search application. The search application must handle queries that have text and images.

Which type of FM should the AI practitioner use to power the search application?

A. Multi-modal embedding model

B. Text embedding model

C. Multi-modal generation model

D. Image generation model

A company is using an Amazon Bedrock base model to summarize documents for an internal use case. The company trained a custom model to improve the summarization quality.

Which action must the company take to use the custom model through Amazon Bedrock?

A. Purchase Provisioned Throughput for the custom model.

B. Deploy the custom model in an Amazon SageMaker endpoint for real-time inference.

C. Register the model with the Amazon SageMaker Model Registry.

D. Grant access to the custom model in Amazon Bedrock.

A medical company is customizing a foundation model (FM) for diagnostic purposes. The company needs the model to be transparent and explainable to meet regulatory requirements.

Which solution will meet these requirements?

A. Configure the security and compliance by using Amazon Inspector.

B. Generate simple metrics, reports, and examples by using Amazon SageMaker Clarify.

C. Encrypt and secure training data by using Amazon Macie.

D. Gather more data. Use Amazon Rekognition to add custom labels to the data.

A company wants to use a pre-trained generative AI model to generate content for its marketing campaigns. The company needs to ensure that the generated content aligns with the company's brand voice and messaging requirements.

Which solution meets these requirements?

A. Optimize the model's architecture and hyperparameters to improve the model's overall performance.

B. Increase the model's complexity by adding more layers to the model's architecture.

C. Create effective prompts that provide clear instructions and context to guide the model's generation.

D. Select a large, diverse dataset to pre-train a new generative model.