- A
Set temperature to 0 in the Azure OpenAI completion request.
Temperature 0 makes output deterministic and grounded in provided context.
- B
Reduce the top_k parameter in the search query to retrieve fewer documents.
Why wrong: Retrieving fewer documents may reduce context but doesn't prevent invention.
- C
Increase the chunk size in the index to provide more context per document.
Why wrong: More context helps but doesn't stop invention if model is creative.
- D
Use Azure OpenAI Service on your own data integration to directly query the SQL database.
Why wrong: Direct integration still uses model; temperature adjustment is key.
AI-102 Implement generative AI solutions Practice Question
This AI-102 practice question tests your understanding of implement generative ai solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
You are a senior AI engineer at a financial services company. You are building a generative AI solution to assist financial advisors with client portfolio recommendations. The solution must use Azure OpenAI Service. The following requirements must be met:
1. Responses must be based on the latest market data and client profiles stored in Azure SQL Database. 2. The solution must not generate investment advice that is not backed by the data. 3. The solution must be cost-effective and minimize API calls. 4. The system must provide citations for the data used in the response.
You design a RAG pattern with Azure AI Search indexing the portfolio data. You also implement a system message instructing the model to only use provided context. However, the model occasionally generates advice that contradicts the data or invents new facts. You need to modify the solution to ensure responses are strictly grounded in the retrieved data. What should you do?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
Set temperature to 0 in the Azure OpenAI completion request.
Option B is correct because setting temperature to 0 makes the model deterministic and less likely to invent. Option A is wrong because lowering top_k still allows creativity. Option C is wrong because adjusting chunk size affects retrieval but not the model's adherence. Option D is wrong because integrating with the data doesn't prevent hallucination if temperature is high.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Set temperature to 0 in the Azure OpenAI completion request.
Why this is correct
Temperature 0 makes output deterministic and grounded in provided context.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
- ✗
Reduce the top_k parameter in the search query to retrieve fewer documents.
Why it's wrong here
Retrieving fewer documents may reduce context but doesn't prevent invention.
- ✗
Increase the chunk size in the index to provide more context per document.
Why it's wrong here
More context helps but doesn't stop invention if model is creative.
- ✗
Use Azure OpenAI Service on your own data integration to directly query the SQL database.
Why it's wrong here
Direct integration still uses model; temperature adjustment is key.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI-102 NAT questions on configuration and troubleshooting.
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement generative AI solutions — This question tests Implement generative AI solutions — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Set temperature to 0 in the Azure OpenAI completion request. — Option B is correct because setting temperature to 0 makes the model deterministic and less likely to invent. Option A is wrong because lowering top_k still allows creativity. Option C is wrong because adjusting chunk size affects retrieval but not the model's adherence. Option D is wrong because integrating with the data doesn't prevent hallucination if temperature is high.
What should I do if I get this AI-102 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI-102 NAT questions on configuration and troubleshooting.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 20, 2026
This AI-102 practice question is part of Courseiva's free Microsoft 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 AI-102 exam.
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