Online Access Free NCP-AAI Exam Questions

An AI architect at a national healthcare provider is maintaining an agentic AI system. The system must monitor model and system performance in real time, raise alerts on failures or anomalies, manage version control and rollback of diagnostic models, and provide transparent insight into agent behavior during patient care workflows.
Which operational approach best supports these requirements using the NVIDIA AI stack?

• A.Containerize each agent in NIM with basic health checks running on cron jobs, and manage version rollback by swapping prebuilt container images.
• B.Optimize all models with TensorRT and use periodic manual log reviews and NVIDIA shell scripts for detecting service anomalies and managing rollback.
• C.Deploy agent models on NVIDIA Triton Inference Server with Prometheus and Grafana for performance alerting, and manage model lifecycle via NGC and the Triton model repository.
• D.Expose agents as stateless NVIDIA API endpoints and monitor activity through application logs, with model versions tracked in a Git-based script repository.

What benefits does a Kubernetes deployment offer over Slurm?

• A.Kubernetes is more optimized for batch jobs to achieve high throughput, and also provides for monitoring and failover in large-scale workloads.
• B.Kubernetes provides autoscaling, auto-restarts, dynamic task scheduling, error isolation with containers, and integrated monitoring.
• C.Kubernetes is the best option for both training and inference, offering advantages for resource management and workload visibility over traditional HPC schedulers like Slurm.

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

An AI agent is being built to execute database queries, generate reports, and interact with cloud services.
Which design choice best improves long-term scalability and maintainability when adding new tools?

• A.Using a plugin-based system with uniform tool registration and invocation
• B.Hardcoding each new tool directly into the agent's core logic
• C.Implementing all tools inside a single large function with many if-else branches
• D.Storing tool parameters as unstructured text parsed at runtime

What NVIDIA framework can be used to train a better agent?

• A.TensorRT-LLM
• B.NeMo-RL
• C.NeMo Guardrails