AI0-001 AI Governance and Ethics Practice Question
A data scientist is training a large language model and wants to reduce the carbon footprint. Which practice is MOST effective for reducing energy consumption during training?
⚠ Common exam trap
A common trap is thinking that finishing faster always saves energy, but using more GPUs increases total power draw, and the energy equation (power × time) often results in higher overall consumption due to parallelization overhead and idle power.
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 model pruning and knowledge distillation
Model pruning reduces the number of parameters in the model, and knowledge distillation trains a smaller student model to mimic a larger teacher model. Both techniques directly reduce the computational operations (FLOPs) required during training and inference, leading to significant energy savings. In contrast, using FP32 or increasing epochs increases energy consumption, and adding more GPUs increases total power draw even if wall-clock time decreases.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use FP32 precision instead of mixed precision
Why it's wrong here
FP32 requires more memory and compute than mixed precision (FP16), increasing energy use.
- ✓
Apply model pruning and knowledge distillation
Why this is correct
Pruning removes unnecessary weights and distillation trains a smaller student model, both reducing the computational load and energy footprint.
- ✗
Use more GPUs in parallel to finish training faster
Why it's wrong here
More GPUs increase total energy consumption even if wall-clock time decreases, unless the workload perfectly scales.
- ✗
Increase the number of training epochs for better accuracy
Why it's wrong here
More epochs mean more computation and thus higher energy consumption.
About these practice questions
One of 754 original AI0-001 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
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.