Master DALL-E’s role in Azure AI Fundamentals (AI-900) with clear examples of text-to-image generation use cases. Learn to identify exam scenarios where generative AI transforms language prompts into visual outputs.
Table of Contents
Question
Which of the following is a suitable scenario for DALL-E models in generative AI?
A. Converting text into numerical vectors for text comparison
B. Generating code completions based on natural language prompts
C. Generation of images based on prompts in natural language
D. Translating natural language text from one language to another
Answer
C. Generation of images based on prompts in natural language
Explanation
The most suitable scenario for DALL-E models in generative AI is the generation of images based on prompts in natural language. DALL-E models are known for their ability to translate textual prompts into corresponding visual outputs.
Converting text into numerical vectors for text comparison is the functionality of embedding models, not DALL-E.
Generating code completions based on natural language prompts is the specialty of GPT models, not DALL-E.
Translating natural language text from one language to another is the function of machine translation models, not DALL-E.
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.