Types of AI - ML, DL, Generative AI, and Agents CAIPM Practice Questions (Page 1)

Questions 1–5

1. 1application · hard

   A financial services firm needs to decide between ML and DL for fraud detection. The data is high-dimensional transaction data with complex, non-linear patterns, but the firm also requires explanations for regulatory audits. What should the firm choose?

   • AUse a simple linear model to ensure full interpretability
   • BUse a deep learning model with post-hoc explainability tools like SHAP
   • CUse a generative model to create synthetic fraud cases for manual review
   • DUse an AI agent to autonomously block transactions without explanation
   Reveal Solution Discussion Select an answer first
2. 2foundation · easy

   Which scenario is best suited for an AI agent rather than a standalone machine learning model?

   • AA model that predicts equipment failure from sensor data
   • BA model that classifies emails as spam or not spam
   • CA model that generates product descriptions from attributes
   • DA system that monitors inventory levels and automatically places orders when stock is low
   Reveal Solution Discussion Select an answer first
4. 3foundation · easy

   What is the primary capability that distinguishes generative AI from other types of AI?

   • AOptimizing a sequence of actions to maximize a reward
   • BCreating new content such as text, images, or audio that resembles training data
   • CMaking decisions autonomously in dynamic environments
   • DClassifying data into predefined categories
   Reveal Solution Discussion Select an answer first
5. 4foundation · easy

   How does an AI agent differ from a typical machine learning model?

   • AAn AI agent requires labeled data, while typical ML models do not
   • BAn AI agent is always deployed in the cloud, while typical ML models run on-premises
   • CAn AI agent always uses deep learning, while typical ML models use simpler algorithms
   • DAn AI agent can take actions in an environment, while a typical ML model only produces predictions or classifications
   Reveal Solution Discussion Select an answer first
6. 5application · medium

   A speech recognition company wants to build a system that transcribes customer service calls in real time, including handling various accents, background noise, and industry-specific jargon. They have a large dataset of recorded calls. Which AI approach is most appropriate?

   • AUse a generative model to create synthetic audio for testing, but not for transcription
   • BUse a traditional ML model with hand-crafted audio features like zero-crossing rate
   • CTrain a deep learning model such as a recurrent neural network or transformer on the audio data
   • DDeploy an AI agent that listens and manually types the transcription
   Reveal Solution Discussion Select an answer first