AI0-001 AI Concepts and Foundations Practice Question
A team deploying an AI model for real-time fraud detection notices that inference latency is too high. The model is a deep neural network with 50 layers, deployed on a cloud GPU. Which of the following is the BEST approach to reduce latency while maintaining acceptable accuracy?
⚠ Common exam trap
CompTIA often tests the misconception that simply upgrading hardware or reducing batch size is the best latency fix, when in fact architectural compression techniques like knowledge distillation are the most effective for deep models with strict latency budgets.
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
✓
Apply knowledge distillation to create a smaller model.
Knowledge distillation trains a smaller 'student' model to mimic the behavior of a larger 'teacher' model, significantly reducing the number of parameters and layers while preserving most of the original accuracy. This directly addresses the high inference latency caused by the 50-layer DNN by producing a compact model that runs faster on the same GPU hardware.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Deploy the model on a more powerful GPU.
Why it's wrong here
This may not reduce latency enough and increases cost.
- ✗
Reduce the batch size for inference.
Why it's wrong here
Smaller batch sizes can increase relative overhead.
- ✗
Replace the DNN with a logistic regression model.
Why it's wrong here
This would likely cause a significant drop in accuracy.
- ✓
Apply knowledge distillation to create a smaller model.
Why this is correct
Correct; distillation compresses the model while preserving performance.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.