Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A financial analyst uses Azure OpenAI Service to generate summaries of quarterly earnings reports. The analyst provides the raw text of the report in the prompt and wants the summary to stick strictly to the facts presented in that text, without adding any external information or speculation. Which technique should the analyst employ to minimize the risk of the model inventing information?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Set the temperature parameter to a high value.
High temperature increases randomness and creativity, which can actually increase the likelihood of the model inventing facts. It does not restrict the model to a provided source.
B
Best answer
Use grounding by including the report text in the prompt and explicitly instructing the model to base the summary only on that text.
Grounding confines the model's response to the content of the provided document, directly addressing the goal of factual accuracy and preventing external knowledge from being introduced.
C
Distractor review
Set the frequency penalty to the maximum allowed value.
A high frequency penalty reduces the repetition of phrases but does not anchor the model to a specific source text; it can still generate ungrounded statements.
D
Distractor review
Set the max_tokens parameter to a very small number.
Limiting max_tokens only truncates the output length; it does not ensure that the output is factually based on the provided text. The model may still generate unsupported content within the token limit.
Common exam trap
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.
Technical deep dive
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.
Related practice questions
Related AI-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
Question 1
A developer wants to build a virtual assistant that can understand user intents such as 'Book a flight' or 'Check weather' and extract relevant entities like destination and date. The developer has a small set of labeled example utterances. Which Azure AI Language feature should the developer use?
Question 2
A developer is building a customer support chatbot using Azure OpenAI. The chatbot should never reveal its system instructions or internal configuration. The developer wants to add a rule at the beginning of the conversation to prevent prompt injection attacks. Which technique should they use?
Question 3
A developer is using Azure OpenAI Service to generate product descriptions from technical specifications. The generated descriptions sometimes include plausible-sounding but incorrect details (hallucinations). The developer wants to ensure the model's responses are strictly based on the provided product data and does not add any external or invented information. Which approach should the developer use?
Question 4
A developer is using Azure OpenAI with GPT-4 to build a chatbot that answers legal questions based on a company's internal policy documents. The developer wants the model's responses to be maximally deterministic and factual, avoiding any creative or speculative language. Which parameter should the developer set to the lowest possible value in the API call?
Question 5
A developer is using Azure OpenAI to generate creative product descriptions. The outputs are often repetitive and lack variety. The developer wants to increase the diversity of the generated text while still keeping it coherent. Which parameter should the developer increase?
Question 6
A developer is using Azure OpenAI Service to generate product descriptions. They want the output to be highly focused and deterministic, with less randomness. Which parameter should they decrease?
FAQ
Questions learners often ask
What does this AI-900 question test?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Use grounding by including the report text in the prompt and explicitly instructing the model to base the summary only on that text. — Grounding is the process of providing the model with a specific source of truth (such as the provided text) and instructing it to base its responses solely on that content. This significantly reduces hallucination (the generation of false or unsubstantiated information). Temperature controls randomness, frequency penalty reduces repetition, and max_tokens limits output length; none of these directly ensure factual adherence to a given text.
What should I do if I get this AI-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
Discussion
Loading comments…
Sign in to join the discussion.