Quiz A_3

A company is training a foundation model (FM). The company wants to increase the accuracy of the model up to a specific acceptance level Which solution will meet these requirements?

• Decrease the batch size

• Increase the epochs

• Decrease the epoxy

• Increase the temperature parameter

A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions Which business objective should the company use to evaluate the effect of the LLM chatbot

• Website engagement rate

• Average call duration

• Corporate social responsibility

• Regulatory compliance

Which functionality does Amazon SageMaker Clarify provide?

• Integrates Retrieval Augmented Generation (RAG) workflow

• Monitors the quality of ML models in production

• Documents critical details about ML models

• Identifies potential bias during data preparation

A company is developing a new model to predict the prices of specific items. The model performed well on the training data set. When the company deployed the model to production, the model's performance decreased significantly What should the company do to mitigate this problem

• Reduce the volume of data that is used in training

• Add hyperparameters to the model

• Increase the volume of data that is used in training

• Increase the model training time

An ecommerce company wants to build a solution to determine customer sentiments based on written customer reviews of products. Which AWS service meet these requirements? (choose two)

• Amazon Lex

• Amazon Comprehend

• Amazon Polly

• Amazon Bedrock

• Amazon Rekognition

A company wants to use large language model (LLMS) with Amazon Bedrock to develop a chat interface for the company's product manuals. These manuals are stored as PDF files Which solution meets these requirements MOST cost-effectively?

• Use prompt engineering to add one PDF file as context to the user prompt when the prompt is submitted to Amazon Bedrock

• Use prompt engineering to add all the PDF files as context to the user prompt when the prompt is submitted to Amazon Bedrock

• Use all the PDF documents to fine-tune a model with Amazon Bedrock. Use fine-tune model to process user prompts

• Upload PDF documents to an Amazon Bedrock knowledge base. Use the knowledge base to provide context when user submit prompts to Amazon Bedrock

A social media company wants to use a large language model (LLM) for content moderation. The company wants to evaluate the LLM outputs for bias and potential discrimination against specific groups or individuals Which data source should the company use to evaluate the LLM outputs with the LEAST administrative effort

• User generated content

• Moderation logs

• Content moderation guidelines

• Benchmark datasets

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 brands voice and messaging requirements Which solution meets these requirements?

• Optimize the model’s architecture and hyperparameters to improve the model's overall performance

• Increase the model's complexity by adding more layers to the model’s architecture

• Create effective prompts that provide clear instructions and context to guide the model’s generation

• Select a large, diverse data set to pre-train a new generative model

A loan company is building a generative AI-based solution to offer new applicants discounts based on specific business criteria. The company wants to build and use an AI model responsibly to minimize bias that could negatively affect some customers Which actions should the company take to meet these requirements? (choose two)

• Detect imbalances or disparities in the data

• Ensure that the model runs frequently

• Evaluate the model's behavior so that the company can provide transparency to stakeholders

• Use the Recall Oriented Understudy for Gisting Evaluation (ROUGE) technique to ensure that the model is 100% accurate

• Ensure that the model’s inference time is within the accepted limits

A company is using an Amazon Bedrock based 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?

• Purchase Provisioned Throughput for the custom model

• Deploy the custom model in Amazon SageMaker endpoint for real-time inference

• Register the model with the Amazon SageMaker Model Registry

• Grant access to in Amazon Bedrock