NCP-AAI 무료 덤프문제 온라인 액세스

You are tasked with deploying a multi-modal agentic system that must respond to user queries with minimal latency while maintaining guardrails for safe and context-aware interactions.
Which of the following configurations best leverages NVIDIA's AI stack to meet these requirements?

• A.Use NIM microservices for deployment, optionally use NeMo Guardrails unless one wants to minimize the inference overhead.
• B.Use NeMo Guardrails for safety, deploy the model with Triton Inference Server using default settings, and rely on hardware accelerators like GPU/TPU inference for cost efficiency.
• C.Integrate NeMo Guardrails, use Omniverse to generate synthetic data, configure NIM microservices for optimized inference, use TensorRT-LLM for deployment, and profile the system using NeMo Agent Toolkit for multi-modal support.
• D.Integrate NeMo Guardrails, configure NIM microservices for optimized inference, use TensorRT-LLM for deployment, and profile the system using Triton Inference Server with multi-modal support.

A company operates agent-based workloads in multiple data centers. They want to minimize latency for users in different regions, maintain continuous service during infrastructure upgrades, and keep operational costs predictable.
Which deployment practice best supports low-latency, resilient, and cost-efficient agent operations at scale?

• A.Schedule regular agent downtime for system updates and operational recalibration.
• B.Implement geo-distributed deployments with rolling updates and resource usage monitoring.
• C.Prioritize high-performance GPUs for all agents in geo-distributed deployments.
• D.Apply static infrastructure allocation with centralized resource usage monitoring at a single data center.

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.Chain-of-thought prompting for reasoning accuracy
• B.Retry logic implementation to ensure robustness during API failures
• C.Use of guardrails to filter out hallucinated content
• D.Multi-modal model integration to handle both text and vision inputs

You are developing a RAG solution and have decided to use a classifier branch as part of your semantic guardrail system to assess the risk of generated text.
Which of the following is a key benefit of using a classifier branch compared to solely relying on prompt filtering?

• A.Classifier branches can automatically adapt to new forms of harmful language.
• B.Since a classifier branch does not require training, it can identify potentially problematic content.
• C.Classifier branches eliminate the need for human oversight, thereby automating the safety process.
• D.Classifier branches primarily focus on detecting factual inaccuracies, rather than stylistic or harmful language.

Which two error handling strategies are MOST important for maintaining agent reliability in production environments? (Choose two.)

• A.Immediate system shutdown for error handling
• B.Circuit breaker patterns for external service calls
• C.Immediate failure propagation to users with verbose logging
• D.Automatic retry with exponential backoff for transient failures