Generative AI Leader Practice Question: Business Strategies for Generative AI Solutions
A manufacturing company wants to use generative AI to create maintenance manuals from sensor data. The manuals must be accurate and reflect the latest equipment configurations. Which approach best ensures data freshness and consistency?
⚠ Common exam trap
Google Cloud often tests the misconception that retraining (Option B) is the only way to keep an LLM current, when in fact RAG provides a more efficient and accurate mechanism for incorporating live data without modifying the model itself.
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 retrieval-augmented generation (RAG) system that queries a live database of sensor configurations.
A retrieval-augmented generation (RAG) system retrieves the most current equipment configurations directly from a live database at inference time, ensuring the generated manual reflects real-time sensor data without requiring model retraining. This approach decouples the static knowledge in the LLM from the dynamic data source, guaranteeing both accuracy and freshness while avoiding the latency and cost of continuous retraining.
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 the model in real-time as sensor data streams in.
Why it's wrong here
Real-time training is computationally expensive and may cause instability.
- ✗
Periodically retrain the model with the latest sensor data.
Why it's wrong here
Retraining cycles may lead to outdated information between updates.
- ✗
Have human technicians review and update the manuals manually.
Why it's wrong here
Manual updates are slow and error-prone.
- ✓
Use a retrieval-augmented generation (RAG) system that queries a live database of sensor configurations.
Why this is correct
RAG ensures responses are based on the most current data.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This Generative AI Leader practice question is part of Courseiva's free Google Cloud 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 Generative AI Leader exam.