Virtual Test Environments for Testing AI-Based Systems CT-AI Practice Questions (Page 7)

Questions 31–34

1. 31foundation · easy

   What is a key consideration when integrating virtual test environments into the overall test process?

   • AAvoiding any real-world testing to reduce costs.
   • BUsing the virtual environment for all testing to save time.
   • CEnsuring that the virtual environment is aligned with the test objectives and requirements.
   • DUsing the virtual environment only for regression testing.
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2. 32foundation · easy

   Which type of virtual test environment provides a virtual replica of a physical system that is continuously updated with real-time data from the physical system?

   • ASimulation environment
   • BEmulation environment
   • CSandbox environment
   • DDigital twin
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4. 33application · medium

   A team is testing an AI model for a self-driving car. They have a simulation environment that models traffic scenarios. However, they notice that the AI performs well in simulation but poorly in real-world tests. What is the most likely cause of this discrepancy?

   • AThe simulation environment has not been validated to accurately represent real-world conditions.
   • BThe team is not using enough test cases in simulation.
   • CThe simulation environment is too complex.
   • DThe AI model is overfitting to the training data.
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5. 34foundation · easy

   Why is synthetic data generation important in virtual test environments?

   • AIt eliminates the need for any real-world data in AI testing.
   • BIt allows the creation of diverse test scenarios that may be rare or unavailable in real-world data.
   • CIt guarantees that the AI model will be unbiased.
   • DIt reduces the need for validating the virtual environment.
   Reveal Solution Discussion Select an answer first