NCP-AAI Practice Questions: Agent Architecture and Design Domain

Correct Answer: A

Explanation: Logging the agent's actions for auditability is crucial for ensuring safety and ethical compliance, as it allows for tracking and reviewing the agent's decisions and actions. Input validation is important but more related to security than safety. Using AI Enterprise is about deployment rather than compliance, and response time optimization is more about performance than safety.

Correct Answer: C

Explanation: The CrewAI framework is specifically designed for collaborative AI tasks, making it suitable for a multi-agent system that requires coordination and task execution. Chain-of-Thought reasoning is more about step-by-step reasoning for individual agents, ReAct patterns focus on reasoning and acting but not specifically on collaboration, and Tree-of-Thoughts is about exploring multiple reasoning paths, which might not directly address coordination.

Correct Answer: C

Explanation: Implementing load balancing across multiple Triton instances ensures that the system can efficiently distribute requests, preventing any single instance from becoming a bottleneck. Option A could lead to inefficiency as a single instance might not handle peak loads well. Option B is more about combining models rather than scaling, and option D might lead to resource underutilization and does not address scaling.

Correct Answer: B

Explanation: Option B is correct because incremental learning allows the agent to update its knowledge base with new data efficiently, without the need for full re-training, which is resource-intensive and time-consuming. Option A is inefficient and not scalable. Option C bypasses integration issues but doesn't solve the underlying problem. Option D is unnecessary if the current framework can be optimized for data integration.

Correct Answer: B

Explanation: The correct answer is B. Embedding ethical guidelines into the agent's decision-making process ensures that ethical considerations are integral to its operations. Relying solely on post-deployment monitoring (A) is reactive rather than proactive. An external rule-based system (C) can be effective but may not cover all scenarios. Optimizing performance metrics (D) does not directly address ethical behavior.

Correct Answer: B

Explanation: Option B is correct because the AIQ Toolkit provides diagnostic tools that can help trace the knowledge integration process, identifying inconsistencies in decision-making. Option A is incorrect as more data does not directly address integration issues. Option C is incorrect because switching frameworks without understanding the problem might not solve it. Option D is incorrect as hyperparameter optimization does not directly address knowledge integration issues.

Correct Answer: C

Explanation: Option C is correct because dynamic batching and concurrent model execution in Triton Inference Server can significantly reduce response times by optimizing resource use and managing loads efficiently. Option A might help but is not as targeted or efficient as using Triton's features. Option B is more about handling query diversity rather than response time optimization. Option D could degrade the agent's performance by oversimplifying the model.

Correct Answer: C

Explanation: Option C is correct because TensorRT-LLM optimizes models specifically for NVIDIA hardware, significantly reducing inference time by optimizing neural network execution. Option A could increase latency by processing larger batches. Option B is more suited for improving accuracy rather than reducing latency. Option D is incorrect as GPU-based deployments typically offer faster inference times compared to CPU-based ones.

Correct Answer: B

Explanation: Option B is correct because the Chain-of-Thought reasoning pattern helps maintain context and continuity over multiple interactions by linking responses logically. Option A, ReAct, is more suited for reactive tasks without maintaining long-term context. Option C, Tree-of-Thoughts, is useful for exploring multiple decision paths but may be complex for simple conversational tasks. Option D lacks the flexibility to adapt to dynamic conversations.

Correct Answer: C

Explanation: Integrating a knowledge graph allows for efficient storage and retrieval of interaction history, enabling the agent to draw connections between past and current interactions. This is more scalable and contextually rich compared to a simple queue or RNN, which may not effectively capture complex interaction patterns. A database system might be too rigid and not optimized for real-time memory recall.