AWS Certified AI Practitioner (AIF-C01) Practice Exam Questions and Answers – Part 8/8

Answer: A. ChatGPT

ChatGPT relies on the transformer architecture, utilizing self-attention mechanisms for natural language tasks. Stable Diffusion and DALL-E are diffusion models primarily used for image generation rather than text.

Answer: D. Artificial Intelligence > Machine Learning > Deep Learning > Generative AI

Artificial intelligence is the broadest category, containing machine learning, which contains deep learning, which enables generative AI. Knowing this nested subset hierarchy is critical for mapping technologies correctly.

Answer: D. Self-supervised learning

Foundation models use self-supervised learning to create labels from input data. Supervised learning requires pre-labeled data sets, whereas reinforcement learning uses reward functions rather than autonomously generating labels.

Answer: B. Use Knowledge Bases for Amazon Bedrock to supplement contextual information from the company's private data to the FM using Retrieval Augmented Generation (RAG)

Knowledge Bases for Amazon Bedrock uses Retrieval Augmented Generation to securely inject private company data into prompts. Fine-tuning alters model weights for general behavior rather than dynamically retrieving specific documents.

Answer: C. Interpretability is about understanding the internal mechanisms of a machine learning model, whereas explainability focuses on providing understandable reasons for the model's predictions and behaviors to stakeholders

Interpretability means a human can understand the internal mechanics driving a model's predictions. Explainability provides stakeholder-friendly justifications for outcomes, especially when the underlying model is too complex to interpret directly.

Answer: D. Data residency is concerned with the physical location of data storage, whereas data retention defines the policies for how long data should be stored and maintained

Data residency refers to the physical or geographical location where data is stored. Data retention dictates the lifecycle policies determining how long data is kept before eventual deletion or archiving.

Answer: A. Machine learning is a subset of artificial intelligence that involves training algorithms to learn from data, while artificial intelligence encompasses a wider range of technologies aimed at simulating human intelligence

Artificial intelligence is the broad discipline of simulating human intelligence, while machine learning is a specific subset focused on algorithms learning from data. A good exam cue is to remember the nesting: machine learning fits inside AI, not the other way around.

Answer: A. Amazon Mechanical Turk provides a marketplace for outsourcing various tasks to a distributed workforce, while Amazon Ground Truth is specifically designed for creating labeled datasets for machine learning, incorporating both automated and human labeling

Amazon Mechanical Turk is a general marketplace for outsourcing microtasks to human workers, whereas Amazon Ground Truth is a dedicated machine learning service for building datasets. Ground Truth uses automation and can route tasks to public, vendor, or private workforces.

Answer: A. The company should use a VPC endpoint for Amazon S3 that allows secure, private connectivity between the VPC and Amazon S3, without the need for an internet connection, ensuring data is transferred securely within the AWS network

A VPC endpoint provides private connectivity between resources inside an isolated VPC and AWS services like Amazon S3. Relying on a NAT gateway or Internet Gateway fails the requirement because those routes still push data traffic over the public internet.

Answer: A. SageMaker Ground Truth enables the creation of high-quality labeled datasets by incorporating human feedback in the labeling process, which can be used to improve reinforcement learning models

SageMaker Ground Truth provides human-in-the-loop capabilities to create high-quality datasets by collecting human feedback, which is essential for reinforcement learning. The other options are incorrect because Ground Truth explicitly relies on human input rather than automated synthetic data generation or real-time decision-making.

Answer: A,C. Validation sets are optional || Test set is used to determine how well the model generalizes

Validation sets are optional and used for hyperparameter tuning during training. Test sets are mandatory for evaluating the final model on unseen data to determine generalization. A strong distractor fails because the test set must never be used for tuning.

Answer: A. The developer should create a rule-based application that uses predefined mathematical rules and formulas to answer probability questions accurately

A rule-based system works best for fundamental math where outcomes rely on strict, predefined formulas. Machine learning is unnecessary here because probability calculations require exact deterministic answers rather than inferred predictions.

Answer: D. Amazon Inspector

Amazon Inspector automatically assesses applications for vulnerabilities and deviations from security best practices. AWS Config tracks resource configuration states, while AWS Artifact supplies compliance reports rather than automated assessments.

Answer: A,B. Medical queries chatbot || Customer service chatbot

Retrieval Augmented Generation powers chatbots needing factual context from private databases, like customer service or medical queries. Creative tasks like original content generation do not require factual data retrieval.

Answer: B. Generative AI is important because it can autonomously create novel and complex data, enhancing creativity and efficiency in various domains

Generative AI is valued because it creates novel, complex data, which boosts creativity and efficiency across diverse fields. Distractors fail because sorting data is a trivial task, and generative AI extends well beyond just gaming and entertainment.