AI0-001 AI Implementation and Operations Practice Question
A company deployed a chatbot using a pre-trained language model. Users report that the chatbot provides incorrect answers to domain-specific questions. Which approach should the AI team prioritize to improve accuracy without retraining the entire model?
⚠ Common exam trap
CompTIA often tests the misconception that increasing temperature reduces randomness (when it actually increases it) or that rolling back to an older version is a valid fix for new domain-specific issues, leading candidates to choose B or D instead of recognizing fine-tuning as the targeted, efficient solution.
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
✓
Fine-tune the model on a curated dataset of domain-specific conversations.
Fine-tuning on a curated domain-specific dataset is the most efficient way to improve accuracy for specialized queries without retraining the entire model. It adjusts the model's weights using a smaller, targeted dataset, preserving general language understanding while adapting to domain terminology and context.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Fine-tune the model on a curated dataset of domain-specific conversations.
Why this is correct
Fine-tuning adapts the model to the domain with less data and compute.
- ✗
Increase the temperature parameter to reduce randomness.
Why it's wrong here
Temperature controls creativity, not factual correctness.
- ✗
Collect more general training data and retrain the model from scratch.
Why it's wrong here
Retraining from scratch is costly and may not address domain specificity.
- ✗
Roll back to a previous version of the model that was more accurate.
Why it's wrong here
Rolling back does not fix the domain knowledge gap.
About these practice questions
Courseiva writes every AI0-001 question from scratch — 754 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. 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.