Question 1

Which of the following parameters can affect the determinism and creativity of an LLM?

Options :

A : All of these options

B : "Top-k" value

C : "Top-p" value

D : "Temperature" value

Answer: A

Question 2

As a GenAI engineer, how would you describe the role of MLOps in managing machine learning systems?

Options :

A : MLOps is exclusively concerned with developing and testing machine learning models before they are deployed into production.

B : MLOps is limited to managing code repositories and version control for machine learning projects.

C : MLOps primarily focuses on automating data collection processes and managing databases for business intelligence.

D : MLOps is automation for managing data, code and models to improve performance, stability and long-term efficiency of ML systems.

Answer: D

Question 3

Why summarizing retrieved documents before feeding them into an AI system is recommended?

Options :

A : To help the AI system to generate responses in multiple languages.

B : To eliminate irrelevant information, making the document shorter.

C : To allow the AI system to process multiple documents simultaneously.

D : To ensure the AI system stays within its context window and focuses on the most essential information.

Answer: D

Question 4

What is a key challenge when implementing reranking in a Retrieval-Augmented Generation (RAG) pipeline for a Gen AI application?

Options :

A : Reranking simplifies the RAG pipeline by reducing the overall complexity and streamlining the process.

B : Reranking requires minimal computational resources, making it an efficient process for large datasets.

C : Reranking eliminates the need for any further processing or adjustments to the retrieved documents before generating a response.

D : Reranking involves multiple calls to the LLM, which can significantly increase both the cost and latency of the RAG chain.

Answer: D

Question 5

As a Gen AI engineer, you are preparing to deploy a large application that integrates multiple LLMs and external GenAI services. What is a critical step to ensure the deployment is successful and the application runs smoothly in production?

Options :

A : Prioritize optimizing each model-s performance before deployment to maximize efficiency.

B : Concentrate on reducing the overall application size to ensure faster deployment and lower resource usage.

C : Package the entire application together, including all models, endpoints, and necessary configurations, to ensure that all components function cohesively as part of a unified deployment pipeline.

D : Focus on deploying each LLM model separately to ensure flexibility and modular updates.

Answer: C