Identify Benefits and Capabilities of Generative AI Solutions AB-731 Practice Questions (Page 5)

Questions 21–25

1. 21expert · hard

   A manufacturing company wants to reduce downtime by predicting equipment failures. They have sensor data from machines, but the data is noisy and contains many false alarms. The company wants to minimize both false positives (unnecessary maintenance) and false negatives (missed failures). What is the most important consideration?

   • AUse a simple rule-based system to detect failures.
   • BFocus on improving data quality by removing all noisy data points.
   • CUse a machine learning model that can handle noisy data and tune the decision threshold to balance precision and recall.
   • DDeploy the model immediately and monitor its performance.
   Reveal Solution Discussion Select an answer first
2. 22application · medium

   A government agency wants to deploy a generative AI system to answer citizen questions about public services. The agency has a large corpus of official documents that are frequently updated. The AI must provide accurate, up-to-date information and cite sources. What is the primary business requirement that grounding must address?

   • AEnsuring the AI can handle a high volume of queries.
   • BEnsuring the AI only uses information from the official documents.
   • CEnsuring the AI is available 24/7.
   • DEnsuring the AI can generate creative responses.
   Reveal Solution Discussion Select an answer first
4. 23application · medium

   A retail company wants to build a machine learning model to predict customer churn. They have historical data from their loyalty program, but the data is heavily skewed toward customers who have already churned. The company wants the model to accurately identify customers who are likely to churn in the next month. What is the most important consideration for this project?

   • AEnsure the training data is representative of the current customer base, including non-churned customers.
   • BUse a larger model architecture to improve accuracy.
   • CDeploy the model immediately and monitor its performance in production.
   • DFocus on prompt engineering to improve the model's predictions.
   Reveal Solution Discussion Select an answer first
5. 24application · medium

   A logistics company wants to use machine learning to optimize delivery routes. The company has years of historical delivery data including traffic patterns, weather, and delivery times. Which scenario best describes the value ML can provide here?

   • AML can replace the need for human dispatchers entirely.
   • BML can automatically update the routing software without human intervention.
   • CML can guarantee the fastest route in all weather conditions.
   • DML can identify complex patterns in historical data to predict optimal routes under varying conditions.
   Reveal Solution Discussion Select an answer first
6. 25foundation · easy

   What is the correct order of the main stages in the machine learning solution lifecycle?

   • AModel deployment, data collection, model training, evaluation, and monitoring
   • BModel evaluation, data preparation, training, deployment, and monitoring
   • CData collection, model deployment, training, evaluation, and monitoring
   • DData collection and preparation, model training, model evaluation, deployment, and monitoring
   Reveal Solution Discussion Select an answer first