CAIC System Architecture & Design 2

Question 1

In an AI system that requires real-time inference with latency under 10ms, which deployment pattern is most appropriate?

Accepted Answer

Edge inference with model quantization

Answer

Edge inference with quantized models minimizes network round-trip latency and enables sub-10ms response times at the point of need.

Question 2

Which architectural pattern best decouples AI model updates from the application logic that consumes predictions?

Accepted Answer

Model-as-a-Service (MaaS) with versioned API contracts

Answer

Model-as-a-Service with versioned APIs allows models to be retrained and deployed independently without changing consumer application code.

Question 3

A feature store in an ML system serves what primary architectural purpose?

Accepted Answer

Providing consistent, reusable feature computations across training and serving

Answer

A feature store eliminates training-serving skew by ensuring the same feature transformations are applied consistently during both model training and online inference.

Question 4

When designing an AI system for a regulated industry, which architectural component directly addresses explainability requirements?

Accepted Answer

Model explanation layer with SHAP or LIME integration

Answer

Integrating post-hoc explainability tools like SHAP or LIME allows the system to generate human-interpretable rationales for individual predictions required by regulators.

Question 5

What is the key advantage of using a shadow deployment strategy when releasing a new AI model?

Accepted Answer

It allows production traffic comparison without exposing users to the new model's outputs

Answer

Shadow deployment runs the new model in parallel on real traffic and logs its outputs for comparison without affecting the user experience, enabling safe pre-production validation.

(CAIC) Certified AI Consultant Practice Test

(CAIC) Certified AI Consultant Practice Test

CAIC System Architecture & Design 2