- A
Train on the largest possible dataset
Why wrong: Larger datasets increase training time and energy use.
- B
Use energy-efficient hardware (e.g., TPUs)
Energy-efficient hardware reduces power consumption.
- C
Use redundant backup servers
Why wrong: Redundant servers increase energy consumption without contributing to efficiency.
- D
Increase batch size to maximum
Why wrong: Larger batch sizes may improve throughput but can increase peak power draw.
- E
Optimize model architecture for lower computational cost
Smaller or more efficient models require less energy to train.
Question 308 of 1,000
AI0-001 AI Governance and Ethics Practice Question
This AI0-001 practice question tests your understanding of ai governance and ethics. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A startup is training a large language model and wants to reduce its environmental impact. Which TWO practices are considered green AI?
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
✓
Use energy-efficient hardware (e.g., TPUs)
Option B is correct because using energy-efficient hardware such as Tensor Processing Units (TPUs) or specialized AI accelerators reduces the power consumption per floating-point operation, directly lowering the carbon footprint of training large language models. This aligns with green AI principles by optimizing the energy-to-performance ratio.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 on the largest possible dataset
Why it's wrong here
Larger datasets increase training time and energy use.
- ✓
Use energy-efficient hardware (e.g., TPUs)
Why this is correct
Energy-efficient hardware reduces power consumption.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use redundant backup servers
Why it's wrong here
Redundant servers increase energy consumption without contributing to efficiency.
- ✗
Increase batch size to maximum
Why it's wrong here
Larger batch sizes may improve throughput but can increase peak power draw.
- ✓
Optimize model architecture for lower computational cost
Why this is correct
Smaller or more efficient models require less energy to train.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that maximizing hardware utilization (e.g., large batch sizes or datasets) is inherently green, when in fact green AI focuses on minimizing total energy consumption and carbon emissions, not just throughput or utilization metrics.
Detailed technical explanation
How to think about this question
Green AI emphasizes model efficiency through techniques like pruning, quantization, and knowledge distillation, which reduce the number of floating-point operations (FLOPs) required. For example, using mixed-precision training with FP16 or bfloat16 on TPUs can halve energy use while maintaining accuracy. Real-world scenarios, such as Google's use of TPU v4 pods for training PaLM, demonstrate that hardware-software co-optimization yields significant energy savings compared to generic GPU clusters.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the AI0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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AI Governance and Ethics — study guide chapter
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FAQ
Questions learners often ask
What does this AI0-001 question test?
AI Governance and Ethics — This question tests AI Governance and Ethics — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use energy-efficient hardware (e.g., TPUs) — Option B is correct because using energy-efficient hardware such as Tensor Processing Units (TPUs) or specialized AI accelerators reduces the power consumption per floating-point operation, directly lowering the carbon footprint of training large language models. This aligns with green AI principles by optimizing the energy-to-performance ratio.
What should I do if I get this AI0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
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.
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