AI-103 Computer Vision Practice Question
You are optimizing an application that calls Azure AI Vision Read API. Which THREE techniques help reduce latency and improve overall throughput? (Choose three.)
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
✓
Resize extremely large images to optimal dimensions while maintaining readability.
Throughput and latency improvements include resizing excessively large images before upload, using asynchronous polling efficiently without tight busy-wait loops, and co-locating resources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Send uncompressed RAW bitmap data to bypass image decoding overhead.
Why it's wrong here
RAW bitmaps increase payload sizes significantly, increasing network latency.
- ✗
Disable SSL/TLS verification to speed up TCP handshakes.
Why it's wrong here
Disabling TLS is insecure and unsupported for Azure endpoints.
- ✓
Resize extremely large images to optimal dimensions while maintaining readability.
Why this is correct
Reducing massive file sizes speeds up network transfer and processing.
- ✓
Implement proper polling intervals (e.g., waiting 1 second between checks) rather than aggressive busy-waiting.
Why this is correct
Proper polling intervals reduce unnecessary HTTP calls and rate limit risk.
- ✓
Co-locate the application hosting and the Azure AI Vision resource in the same Azure region.
Why this is correct
Co-location minimizes network round-trip time.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-103 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-103 exam.