Question 200 of 1,020

Describe features of computer vision workloads on Azure →mediumMultiple ChoiceObjective-mapped

AI-900 Practice Question: Describe features of computer vision workloads on Azure

This AI-900 practice question tests your understanding of describe features of computer vision 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.

What is 'Azure AI Custom Vision' and how does it differ from Azure AI Vision?

A
Azure AI Vision is for video; Custom Vision is for still images only
Why wrong: Both services can work with images — the distinction is pre-built general models vs. custom-trained domain-specific models.
B
Azure AI Vision offers pre-built general models; Custom Vision lets you train models for your specific categories
Custom Vision trains on your labelled images for domain-specific classification or detection — while Azure AI Vision's models are general-purpose.
C
Custom Vision is more expensive because it uses more advanced AI algorithms
Why wrong: Pricing differs but the key distinction is customisability — Custom Vision is trained on your data, not superior algorithms.
D
Azure AI Vision requires GPU compute; Custom Vision runs on CPU only
Why wrong: Hardware requirements are implementation details — the key distinction is pre-built general vs. custom-trained domain-specific models.

Full breakdown with real-world context →

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

✓

Azure AI Vision offers pre-built general models; Custom Vision lets you train models for your specific categories

Azure AI Vision provides pre-trained models for common computer vision tasks like object detection, OCR, and image analysis without requiring custom training data. Azure AI Custom Vision, on the other hand, allows you to upload your own labeled images and train a model to recognize specific categories or objects that are unique to your business scenario. This distinction makes B correct because it highlights the key difference: pre-built general models versus custom-trained models.

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.

✗
Azure AI Vision is for video; Custom Vision is for still images only
Why it's wrong here
Both services can work with images — the distinction is pre-built general models vs. custom-trained domain-specific models.
✓
Azure AI Vision offers pre-built general models; Custom Vision lets you train models for your specific categories
Why this is correct
Custom Vision trains on your labelled images for domain-specific classification or detection — while Azure AI Vision's models are general-purpose.
Related concept
Read the scenario before looking for a memorised answer.
✗
Custom Vision is more expensive because it uses more advanced AI algorithms
Why it's wrong here
Pricing differs but the key distinction is customisability — Custom Vision is trained on your data, not superior algorithms.
✗
Azure AI Vision requires GPU compute; Custom Vision runs on CPU only
Why it's wrong here
Hardware requirements are implementation details — the key distinction is pre-built general vs. custom-trained domain-specific models.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse 'Custom Vision' with being a more advanced or expensive version of Azure AI Vision, when in fact the core distinction is about customization versus pre-built functionality, not cost or hardware requirements.

Detailed technical explanation

How to think about this question

Under the hood, Azure AI Custom Vision uses transfer learning from a pre-trained neural network (e.g., ResNet or MobileNet) and fine-tunes it on your custom dataset, which allows training with relatively few images. The service automatically handles data augmentation, hyperparameter tuning, and model export to formats like TensorFlow, ONNX, or Docker for edge deployment. In contrast, Azure AI Vision relies on a fixed, Microsoft-managed model that cannot be retrained, making it ideal for general scenarios like brand detection or adult content moderation but inflexible for niche use cases.

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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this AI-900 question test?

Describe features of computer vision workloads on Azure — This question tests Describe features of computer vision workloads on Azure — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Azure AI Vision offers pre-built general models; Custom Vision lets you train models for your specific categories — Azure AI Vision provides pre-trained models for common computer vision tasks like object detection, OCR, and image analysis without requiring custom training data. Azure AI Custom Vision, on the other hand, allows you to upload your own labeled images and train a model to recognize specific categories or objects that are unique to your business scenario. This distinction makes B correct because it highlights the key difference: pre-built general models versus custom-trained models.

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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