- A
Use a high-core-count CPU with large RAM
Why wrong: CPUs are inefficient for parallel matrix operations common in deep learning; training would be very slow.
- B
Use a cluster of GPUs with data parallelism
GPUs accelerate parallel tensor operations, and data parallelism distributes batches across multiple GPUs, significantly reducing training time.
- C
Use a single GPU with model parallelism
Why wrong: Model parallelism might be needed for extremely large models, but for most transformers, data parallelism on multiple GPUs is more straightforward and effective.
- D
Use a single TPU with model parallelism
Why wrong: TPU is specialized but less flexible; single TPU may not provide enough compute for large models, and model parallelism adds complexity.
Question 82 of 1,000
AI0-001 AI Infrastructure and Technologies Practice Question
This AI0-001 practice question tests your understanding of ai infrastructure and technologies. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 machine learning team is training a large transformer model on a text corpus. They need to reduce training time while maintaining model accuracy. Which hardware configuration would be MOST effective for this task?
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 a cluster of GPUs with data parallelism
GPUs are optimized for the parallel computations required in deep learning training, offering significant speedups over CPUs. TPUs are also effective but less accessible and more specialized. The question specifies 'most effective' for training a transformer model, which aligns with GPU acceleration.
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.
- ✗
Use a high-core-count CPU with large RAM
Why it's wrong here
CPUs are inefficient for parallel matrix operations common in deep learning; training would be very slow.
- ✓
Use a cluster of GPUs with data parallelism
Why this is correct
GPUs accelerate parallel tensor operations, and data parallelism distributes batches across multiple GPUs, significantly reducing training time.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use a single GPU with model parallelism
Why it's wrong here
Model parallelism might be needed for extremely large models, but for most transformers, data parallelism on multiple GPUs is more straightforward and effective.
- ✗
Use a single TPU with model parallelism
Why it's wrong here
TPU is specialized but less flexible; single TPU may not provide enough compute for large models, and model parallelism adds complexity.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 AI0-001 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this AI0-001 question test?
AI Infrastructure and Technologies — This question tests AI Infrastructure and Technologies — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use a cluster of GPUs with data parallelism — GPUs are optimized for the parallel computations required in deep learning training, offering significant speedups over CPUs. TPUs are also effective but less accessible and more specialized. The question specifies 'most effective' for training a transformer model, which aligns with GPU acceleration.
What should I do if I get this AI0-001 question wrong?
Identify which AI0-001 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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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