AI-900 Practice Question: Describe features of generative AI workloads on Azure
This AI-900 practice question tests your understanding of describe features of generative ai workloads on azure. 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.
A marketing team uses Azure OpenAI Service to generate tagline options for a new product. They notice that the model often generates very similar taglines for the same prompt, lacking creativity. To increase the diversity and variety of the output, which parameter should they increase?
Increasing temperature makes the model more creative and varied by increasing randomness in token selection.
B
Top P
Why wrong: Top P (nucleus sampling) also affects diversity, but temperature is the more direct parameter for increasing randomness and variability.
C
Frequency penalty
Why wrong: Frequency penalty reduces the repetition of words and phrases, but it does not directly increase overall creativity or diversity; it targets repetition.
D
Max tokens
Why wrong: Max tokens limits the length of the output, which does not affect the diversity of the generated content.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Temperature
Increasing the temperature parameter makes the model's output more random and diverse by scaling the probability distribution over possible next tokens. A higher temperature (e.g., 0.9) flattens the distribution, giving lower-probability tokens a better chance to be selected, which directly addresses the lack of creativity and variety in the generated taglines.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Temperature
Why this is correct
Increasing temperature makes the model more creative and varied by increasing randomness in token selection.
Related concept
Read the scenario before looking for a memorised answer.
✗
Top P
Why it's wrong here
Top P (nucleus sampling) also affects diversity, but temperature is the more direct parameter for increasing randomness and variability.
✗
Frequency penalty
Why it's wrong here
Frequency penalty reduces the repetition of words and phrases, but it does not directly increase overall creativity or diversity; it targets repetition.
✗
Max tokens
Why it's wrong here
Max tokens limits the length of the output, which does not affect the diversity of the generated content.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse temperature with Top P, thinking both control randomness equally, but temperature directly scales the probability distribution for randomness, while Top P controls the size of the candidate token set via cumulative probability threshold.
Trap categories for this question
Keyword trap
Frequency penalty reduces the repetition of words and phrases, but it does not directly increase overall creativity or diversity; it targets repetition.
Command / output trap
Max tokens limits the length of the output, which does not affect the diversity of the generated content.
Detailed technical explanation
How to think about this question
Under the hood, temperature is applied by dividing the logits (raw scores) by the temperature value before passing them through a softmax function; a temperature of 1.0 leaves the distribution unchanged, while values above 1.0 (e.g., 2.0) make the distribution more uniform, increasing entropy. In practice, for creative tasks like tagline generation, a temperature between 0.7 and 1.2 is often used to balance coherence and variety, while values above 1.5 can lead to incoherent or nonsensical outputs. A real-world scenario is generating marketing slogans where a temperature of 0.8 might yield a few distinct options, but increasing to 1.0 produces more unexpected and diverse phrases.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AI-900 question in full detail.
Describe features of generative AI workloads on Azure — This question tests Describe features of generative AI workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Temperature — Increasing the temperature parameter makes the model's output more random and diverse by scaling the probability distribution over possible next tokens. A higher temperature (e.g., 0.9) flattens the distribution, giving lower-probability tokens a better chance to be selected, which directly addresses the lack of creativity and variety in the generated taglines.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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