AI-102 Implement generative AI solutions Practice Question
Your company wants to build a custom generative AI model that generates architectural designs. The model should be trained on the company's proprietary dataset of floor plans and designs. Which Azure service should you use?
⚠ Common exam trap
Test-takers frequently confuse 'fine-tuning' (offered by Azure OpenAI Service) with 'custom training from scratch' (offered by Azure Machine Learning), leading them to incorrectly select Azure OpenAI Service when the question explicitly requires training a model on proprietary data with custom architecture.
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 Machine Learning
Azure Machine Learning is the correct service because it provides a comprehensive platform for training custom generative AI models using your own proprietary datasets. It supports deep learning frameworks like PyTorch and TensorFlow, enabling you to build, train, and deploy a custom generative model for architectural designs, whereas Azure OpenAI Service is limited to pre-trained models and fine-tuning, not custom training from scratch.
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 OpenAI Service
Why it's wrong here
Azure OpenAI provides pre-trained models; you cannot train custom models from scratch.
- ✓
Azure Machine Learning
Why this is correct
Azure Machine Learning supports training custom generative models using your own data.
- ✗
Azure AI Vision
Why it's wrong here
Azure AI Vision is for image classification, object detection, etc., not for generative tasks.
- ✗
Azure AI Document Intelligence
Why it's wrong here
This service is for document analysis and extraction, not generative model training.
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