Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
A company uses Azure OpenAI Service to generate marketing copy for social media posts. They want to prevent the model from producing content that contains offensive language, harmful stereotypes, or violent themes that go against their brand guidelines. Which feature should the company configure within Azure OpenAI Service?
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
Fine-tuning the model with a custom dataset
Fine-tuning trains the model on specific data to improve performance on a task. However, it does not inherently filter out objectionable content; the model might still generate harmful text if the fine-tuning data contains such patterns.
B
Best answer
Configuring the content filtering (responsible AI filters)
Azure OpenAI’s content filtering system is a built-in safeguard that automatically screens inputs and outputs for categories like hate, violence, sexual content, and self-harm. Companies can configure severity levels to prevent undesirable content from being generated.
C
Distractor review
Increasing the token limit per response
Token limits control the maximum length of the text generated (e.g., 200 tokens). They do not prevent the model from producing harmful content; they only limit how long the output can be.
D
Distractor review
Using prompt engineering techniques
Prompt engineering (e.g., adding instructions like 'do not use bad language') can help guide the model, but it is not a guaranteed safety mechanism. The model may still generate inappropriate content if the instruction is not perfectly followed. Content filtering is the official safeguard.
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: Configuring the content filtering (responsible AI filters) — Azure OpenAI Service includes a content filtering system that detects and blocks harmful categories of content such as hate, violence, sexual, and self-harm. Fine-tuning adapts a model to a specific task but does not guarantee blocking undesired outputs. Prompt engineering can reduce harmful outputs by careful phrasing, but is not a reliable safety mechanism alone. Token limits restrict the length of output, not the nature of the content.
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.
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