This Generative AI Leader practice question tests your understanding of fundamentals of generative ai. 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 team is building a medical diagnosis assistant using a foundation model. To comply with regulations, they need to ensure the model does not make up facts. What is the best approach?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Use a small model to hallucinate less
Why wrong: Small models also hallucinate and may lack medical knowledge.
Use grounding with Vertex AI Search
Grounding provides verifiable citations and reduces fabrication.
Reduce temperature to 0
Why wrong: Zero temperature makes outputs deterministic but does not ensure truthfulness.
Fine-tune on medical journals
Why wrong: Fine-tuning does not guarantee factuality and may still hallucinate.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Use grounding with Vertex AI Search
Grounding with Vertex AI Search is the best approach because it connects the foundation model's outputs to a verifiable, curated knowledge base, ensuring factual accuracy and compliance with regulations that prohibit hallucination. By retrieving information from a trusted source (e.g., medical databases) in real time, the model can cite evidence and avoid generating unverified claims.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Use a small model to hallucinate less
Why it's wrong here
Small models also hallucinate and may lack medical knowledge.
Use grounding with Vertex AI Search
Why this is correct
Grounding provides verifiable citations and reduces fabrication.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Reduce temperature to 0
Why it's wrong here
Zero temperature makes outputs deterministic but does not ensure truthfulness.
Fine-tune on medical journals
Why it's wrong here
Fine-tuning does not guarantee factuality and may still hallucinate.
Common exam traps
Google Cloud often tests the misconception that reducing temperature or using a smaller model can eliminate hallucination, when in fact only grounding with external, verifiable data sources can reliably prevent fact fabrication in high-stakes domains.
Trap categories for this question
Command / output trap
Zero temperature makes outputs deterministic but does not ensure truthfulness.
Detailed technical explanation
Grounding with Vertex AI Search uses retrieval-augmented generation (RAG), where the model queries an external index (e.g., a vector database or structured knowledge base) at inference time to retrieve relevant, up-to-date documents. This approach decouples factual recall from parametric memory, allowing the model to cite sources and reduce hallucination even when the underlying foundation model has not seen the specific data. In regulated industries like healthcare, this is critical because it provides an auditable trail of evidence for each generated statement.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Fundamentals of Generative AI — This question tests Fundamentals of Generative AI — Read the scenario before looking for a memorised answer..
The correct answer is: Use grounding with Vertex AI Search — Grounding with Vertex AI Search is the best approach because it connects the foundation model's outputs to a verifiable, curated knowledge base, ensuring factual accuracy and compliance with regulations that prohibit hallucination. By retrieving information from a trusted source (e.g., medical databases) in real time, the model can cite evidence and avoid generating unverified claims.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
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.
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