AI0-001 AI Concepts and Techniques Practice Question
A company is deploying a text generation model for customer service emails. They want to ensure the model's responses are factual and based on internal knowledge bases. Which technique is most effective?
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 Retrieval-Augmented Generation (RAG)
RAG retrieves relevant documents from the knowledge base at inference time, grounding the model's responses in facts. Prompt engineering alone can't ensure factual accuracy; fine-tuning may still hallucinate; temperature reduction only reduces randomness.
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 Retrieval-Augmented Generation (RAG)
Why this is correct
RAG retrieves relevant knowledge base content at query time, providing the model with factual context to generate accurate responses.
- ✗
Fine-tune the model on historical customer service emails
Why it's wrong here
Fine-tuning on historical emails may not include the latest knowledge base information and can still produce hallucinations.
- ✗
Write a detailed system prompt
Why it's wrong here
System prompts guide behavior but cannot inject specific knowledge; the model still relies on its internal parameters.
- ✗
Set the temperature to 0
Why it's wrong here
Temperature controls randomness, not factual grounding; even with temperature=0, the model may hallucinate.
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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.