CAIC System Architecture & Design 3

Question 1

A company wants to serve multiple AI use cases (recommendation, fraud detection, NLP) from a single platform. Which architectural approach best enables this?

Accepted Answer

An AI platform with shared infrastructure, common SDKs, and modular ML pipelines

Answer

A unified AI platform with shared infrastructure and tooling reduces duplication, standardizes best practices, and enables teams to focus on their specific models rather than platform concerns.

Question 2

What distinguishes an online learning system from a batch retraining system in AI architecture?

Accepted Answer

Online learning updates the model incrementally with each new data point or mini-batch in production

Answer

Online learning continuously updates model parameters using a stream of incoming examples, allowing the model to adapt to distribution shifts without full retraining cycles.

Question 3

Which pattern addresses the challenge of serving recommendations to millions of users with sub-100ms latency?

Accepted Answer

Two-stage retrieval: fast approximate nearest-neighbor retrieval followed by a lightweight re-ranker

Answer

Two-stage systems use efficient ANN search to narrow candidates quickly, then apply a more accurate but lightweight model to rank only those candidates, achieving both speed and quality.

Question 4

In a microservices-based AI system, what is the primary risk of tight coupling between the prediction service and the data preprocessing service?

Accepted Answer

Changes to preprocessing logic can break the prediction service without clear version boundaries

Answer

Tight coupling means that changes in one service's interface or behavior directly impact dependent services, violating the independent deployability principle of microservices.

Question 5

Which database type is most architecturally suited as a vector store for similarity search in a RAG (Retrieval-Augmented Generation) system?

Accepted Answer

Purpose-built vector database with ANN index support like Pinecone or Weaviate

Answer

Purpose-built vector databases use specialized ANN indexes (HNSW, IVF) that enable efficient high-dimensional similarity search, which is the core operation in RAG retrieval.

(CAIC) Certified AI Consultant Practice Test

(CAIC) Certified AI Consultant Practice Test

CAIC System Architecture & Design 3