easymultiple choiceObjective-mapped

A company wants to build a chatbot that can engage in free-form conversations with customers, answering questions and providing information without being limited to a fixed set of responses. Which type of AI model is most suitable?

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A company wants to build a chatbot that can engage in free-form conversations with customers, answering questions and providing information without being limited to a fixed set of responses. Which type of AI model is most suitable?

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

Classification model

Classification models predict discrete categories (e.g., spam vs. not spam) and cannot generate varied conversational responses.

B

Distractor review

Regression model

Regression models predict continuous numeric values, such as temperature or price, not conversational text.

C

Best answer

Generative language model

Generative language models can produce coherent, context-aware text and are ideal for free-form conversational AI.

D

Distractor review

Object detection model

Object detection identifies and locates objects within images, not suitable for generating text responses.

Common exam trap

Common exam trap: answer the scenario, not the keyword

Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.

Technical deep dive

How to think about this question

This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.

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.
  • Use explanations to understand the rule behind the answer.

TExam Day Tips

  • Underline the problem statement mentally.
  • 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.

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?

Read the scenario before looking for a memorised answer.

What is the correct answer to this question?

The correct answer is: Generative language model — Generative language models, such as GPT (Generative Pre-trained Transformer), are designed to produce human-like text and can adapt to a wide range of conversational inputs. Classification models assign predefined labels, regression models predict numeric values, and object detection models locate objects in images — none are suited for open-ended conversation.

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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