AIF-C01 Online Practice Questions and Answers

Correct Answer: AC

To build an AI model responsibly and minimize bias, it is essential to ensure fairness and transparency throughout the model development and deployment process. This involves detecting and mitigating data imbalances and thoroughly

evaluating the model's behavior to understand its impact on different groups.

Option A (Correct): "Detect imbalances or disparities in the data":This is correct because identifying and addressing data imbalances or disparities is a critical step in reducing bias. AWS provides tools like Amazon SageMaker Clarify to detect

bias during data preprocessing and model training. Option C (Correct): "Evaluate the model's behavior so that the company can provide transparency to stakeholders":This is correct because evaluating the model's behavior for fairness and

accuracy is key to ensuring that stakeholders understand how the model makes decisions. Transparency is a crucial aspect of responsible AI.

Option B:"Ensure that the model runs frequently" is incorrect because the frequency of model runs does not address bias.

Option D:"Use the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) technique to ensure that the model is 100% accurate" is incorrect because ROUGE is a metric for evaluating the quality of text summarization models, not for

minimizing bias.

Option E:"Ensure that the model's inference time is within the accepted limits" is incorrect as it relates to performance, not bias reduction.

AWS AI Practitioner References:

Amazon SageMaker Clarify:AWS offers tools such as SageMaker Clarify for detecting bias in datasets and models, and for understanding model behavior to ensure fairness and transparency.

Responsible AI Practices:AWS promotes responsible AI by advocating for fairness, transparency, and inclusivity in model development and deployment.

Correct Answer: A

Creating a prompt template that teaches the LLM to detect attack patterns is the most effective way to reduce the risk of the model being manipulated through prompt engineering.

Correct Answer: A

Amazon SageMaker Serverless Inference is the correct solution for deploying an ML model to production in a way that allows a web application to use the model without the need to manage the underlying infrastructure.

Amazon SageMaker Serverless Inferenceprovides a fully managed environment for deploying machine learning models. It automatically provisions, scales, and manages the infrastructure required to host the model, removing the need for the

company to manage servers or other underlying infrastructure.

Correct Answer: C

An anomaly detection system is suitable for identifying unusual patterns or behaviors, such as suspicious IP addresses, which might indicate a potential threat.

Correct Answer: A

BLEU (Bilingual Evaluation Understudy) is a metric used to evaluate the accuracy of machine-generated translations by comparing them against reference translations. It is commonly used for translation tasks to measure how close the

generated output is to professional human translations.

Option A (Correct): "Bilingual Evaluation Understudy (BLEU)":This is the correct answer because BLEU is specifically designed to evaluate the quality of translations, making it suitable for the company's use case. Option B:"Root mean

squared error (RMSE)" is incorrect because RMSE is used for regression tasks to measure prediction errors, not translation quality. Option C:"Recall-Oriented Understudy for Gisting Evaluation (ROUGE)" is incorrect as it is used to evaluate

text summarization, not translation. Option D:"F1 score" is incorrect because it is typically used for classification tasks, not for evaluating translation accuracy.

AWS AI Practitioner

References:

Model Evaluation Metrics on AWS:AWS supports various metrics like BLEU for specific use cases, such as evaluating machine translation models.

Correct Answer: A

Providing labeled data with both a prompt field and a completion field is the correct strategy for fine-tuning a foundation model (FM) on Amazon Bedrock.

Correct Answer: A

Object detection is the correct strategy for automatically identifying and categorizing animals in photos.

Correct Answer: A

A multi-modal embedding model is the correct type of foundation model (FM) for powering a search application that handles queries containing both text and images.

Correct Answer: A

Tokens in generative AI models are the smallest units that the model processes, typically representing words, subwords, or characters. They are essential for the model to understand and generate language, breaking down text into

manageable parts for processing.

Option A (Correct): "Tokens are the basic units of input and output that a generative AI model operates on, representing words, subwords, or other linguistic units":This is the correct definition of tokens in the context of generative AI models.

Option B:"Mathematical representations of words" describes embeddings, not tokens.

Option C:"Pre-trained weights of a model" refers to the parameters of a model, not tokens.

Option D:"Prompts or instructions given to a model" refers to the queries or commands provided to a model, not tokens.

AWS AI Practitioner

References:

Understanding Tokens in NLP:AWS provides detailed explanations of how tokens are used in natural language processing tasks by AI models, such as in Amazon Comprehend and other AWS AI services.

Correct Answer: B

Amazon SageMaker Clarify provides transparency and explainability for machine learning models by generating metrics, reports, and examples that help to understand model predictions. For a medical company that needs a foundation model to be transparent and explainable to meet regulatory requirements, SageMaker Clarify is the most suitable solution.