AI0-001 AI Infrastructure and Technologies Practice Question
A hospital's radiology department wants to run a diagnostic imaging model inside its own data center because patient images cannot leave the premises. The team needs to manage model versions, roll back a bad deployment quickly, and keep an audit trail of which model version produced each prediction. Which approach best satisfies these requirements?
⚠ Common exam trap
The trap here is treating version control as simply keeping old files around, when the audit requirement demands that each prediction record the exact immutable version that produced it.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Serve the model from an internal model registry with versioned artifacts and log the model version with each prediction.
Keeping the model in an internal registry preserves data residency while giving the team immutable versions for promotion and rollback. Logging the model version with every prediction produces the traceability regulators and clinicians need, so a questionable result can be tied to a specific artifact rather than to an undifferentiated deployment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Copy the model file onto each radiologist workstation and run inference locally with a desktop script.
Why it's wrong here
Copying the model to workstations destroys centralized version control, so different machines can silently run different models and there is no reliable rollback path. A desktop script also produces no consolidated audit log, and updating a model would require touching every workstation, which is operationally unmanageable for a clinical deployment.
- ✗
Host the model on a public inference API and send only anonymized image hashes for scoring.
Why it's wrong here
Even anonymized hashes leave the premises and the diagnostic decision would depend on an external service, which violates the requirement that images and inference stay inside the data center. It also gives the hospital no control over model versioning, so rolling back a bad deployment would depend on the vendor's release cycle rather than the team's own registry.
- ✓
Serve the model from an internal model registry with versioned artifacts and log the model version with each prediction.
Why this is correct
An internal model registry keeps every artifact on-premises, assigns immutable versions, and lets the team promote or roll back a deployment by pointing the serving layer at a different version. Recording the version alongside each prediction creates the audit trail the department needs to trace any diagnostic output back to the exact model that produced it.
- ✗
Store the model in a shared network folder and have the serving application load whichever file has the newest timestamp.
Why it's wrong here
Selecting a model by file timestamp is not versioning; a stray copy or a clock skew can promote an unintended artifact, and there is no record of which model served a given request. The absence of immutable version identifiers makes rollback guesswork and prevents the audit trail the radiology department requires.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.