AI0-001 Implementing AI Solutions Practice Question
An AI system uses a pre-trained image classification model to detect defects in manufacturing. The team wants to deploy the model in an edge device with limited GPU memory. Which technique should they consider first?
⚠ Common exam trap
The AI0-001 exam often tests the misconception that increasing batch size or model size improves performance in resource-constrained environments, when in fact these actions increase memory demand and are counterproductive for edge deployment.
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 quantization to reduce model size
Quantization reduces the precision of the model's weights and activations (e.g., from 32-bit floating point to 8-bit integer), which significantly shrinks the model size and memory footprint while often maintaining acceptable accuracy. This is the most direct and effective first step for deploying a pre-trained model on an edge device with limited GPU memory, as it requires no retraining and immediately addresses the memory constraint.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Train the model from scratch using a smaller dataset
Why it's wrong here
Training from scratch does not guarantee reduced memory and is time-consuming.
- ✓
Apply quantization to reduce model size
Why this is correct
Quantization reduces memory footprint and speeds up inference on edge devices.
- ✗
Use a larger model with more parameters for higher accuracy
Why it's wrong here
Larger models require more memory.
- ✗
Increase the batch size to improve throughput
Why it's wrong here
Larger batch size increases memory usage, which is unsuitable for limited memory.
About these practice questions
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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.