Test Environments for AI-Based Systems CT-AI Practice Questions (Page 8)

Questions 36–40

1. 36application · medium

   A software company wants to automatically test a new version of an AI model every time the code is changed in the repository. The tests should run in a dedicated test environment and the results should be reported back to the development team. What is the best way to achieve this?

   • ARun tests only when a release candidate is created.
   • BManually run the tests after each code change and share results via email.
   • CUse a separate test environment that is not connected to the code repository.
   • DIntegrate the test environment with a CI/CD pipeline that triggers tests on every code commit.
   Reveal Solution Discussion Select an answer first
2. 37foundation · easy

   What is the purpose of containerization when deploying AI models in a test environment?

   • ATo increase the model's accuracy
   • BTo replace the need for testing
   • CTo package the model and its dependencies into a consistent, portable unit
   • DTo automatically generate training data
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4. 38foundation · easy

   What is a compliance consideration when using personal data in an AI test environment?

   • AEnsuring data is anonymized or pseudonymized where required by regulations
   • BStoring all data in a single location regardless of legal requirements
   • CSharing data freely with all team members
   • DDeleting all logs to avoid storing personal data
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5. 39application · medium

   A startup is setting up its first AI test environment. They have limited budget and need to test a model that requires large amounts of data and compute. They are concerned about the cost of maintaining a separate test environment. What is a best practice to address this challenge?

   • ASkip testing and deploy directly to production to save money.
   • BBuy dedicated on-premises hardware for testing to ensure performance.
   • CUse the production environment for testing to avoid extra costs.
   • DUse a cloud-based test environment that can be scaled up during testing and scaled down when idle.
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6. 40foundation · easy

   What is the primary purpose of monitoring tools in an AI test environment?

   • ATo track system performance and model behavior in real time
   • BTo generate synthetic test data
   • CTo version control the training data
   • DTo manage user access to the environment
   Reveal Solution Discussion Select an answer first