Free NVIDIA NCP-AAI Exam Questions

Question 1

You are designing an AI agent for summarizing medical documents that include images and text as well. It must extract key information and recognize dates. Which feature is most critical for ensuring the agent performs well across multiple input and output formats?

A : Use of guardrails to filter out hallucinated content

B : Retry logic implementation to ensure robustness during API failures

C : Chain-of-thought prompting for reasoning accuracy

D : Multi-modal model integration to handle both text and vision inputs

Answer: D

Question 2

In a global financial firm, an AI Architect is building a multi-agent compliance assistant using an agentic AI framework. The system must manage short-term memory for multi-turn interactions and long-term memory for persistent user and policy context. It should enable contextual recall and adaptation across sessions using NVIDIA’s tool stack. Which architectural approach best supports these requirements?

A : Leverage NVIDIA NeMo Framework with modular memory management, integrating conversationalstate tracking, knowledge graphs, and vector store retrieval, while using LoRA-tuned models to adaptresponses overtime.

B : Leverage RAPIDS cuDF for memory tracking by streaming multi-turn conversation logs as GPUresident data frames, assuming transactional history can be recalled and reasoned over using dataframeoperations.

C : Rely exclusively on TensorRT to encode all prior knowledge into compiled model weights, allowinginference-only execution with no external memory dependencies across sessions.

D : Leverage NVIDIA Triton Inference Server with dynamic batching to cache session-level inputsbetween inference calls, and use an external Redis store for long-term memory.

Answer: A

Question 3

You are designing the architecture for a RAG (Retrieval-Augmented Generation) system, and you are concerned about ensuring data freshness and minimizing latency. Which of the following is the most important consideration when designing the architecture?

A : Employing a consolidated architecture with a large service handling all data retrieval and LLMinteraction. This ensures consistent performance and simplifies debugging.

B : Using a synchronous, block-level approach, where the LLM continuously monitors the database forupdates and retrieves the entire dataset with each prompt.

C : Implementing a single, centralized database for all data, updated with a synchronous polling mechanismfor the LLM to retrieve the latest information.

D : Use a loosely coupled, event-driven micro-service architecture where separate services handle dataindexing, retrieval, and LLM prompting.

Answer: D

Question 4

You’re managing an agentic AI responsible for customer support ticket triage. The agent has been consistently accurate in routing tickets to the appropriate departments. However, a team leader has noticed a significant increase in the number of tickets requiring “escalation” – cases where the agent initially misclassified a complex issue as a simple, routine one, leading to delays and frustrated customers. What would be an appropriate first step in resolving this issue?

A : Analyzing the agent’s decision-making process, focusing on the specific criteria it uses to classifytickets, and identifying potential biases or blind spots.

B : Adjusting the agent’s reward function to prioritize speed of resolution over accuracy, as a first step inanalysis of the problem.

C : Increasing the agent’s autonomy, granting it more decision-making power during triage to improve itsefficiency.

D : Conducting a “red-teaming” exercise, having human agents deliberately create complex and ambiguousscenarios to analyze the agent’s robustness.

Answer: A

Question 5

An AI Engineer has deployed a multi-agent system to manage supply chain logistics. Stakeholders request greater insight into how the agents decide on actions across tasks. Which approach would best improve decision transparency without modifying the underlying model architecture?

A : Gather structured user evaluations after each completed subtask

B : Generate visual summaries of attention patterns for every decision

C : Record a step-by-step reasoning log throughout each agent workflow

D : Retain and share the full sequence of task instructions with stakeholders

Answer: C