Exam NCA-AIIO Topic 2 Question 16 Discussion

Actual exam question for NVIDIA's NCA-AIIO exam
Question #: 16
Topic #: 2

Your company is running a distributed AI application that involves real-time data ingestion from IoT devices spread across multiple locations. The AI model processing this data requires high throughput and low latency to deliver actionable insights in near real-time. Recently, the application has been experiencing intermittent delays and data loss, leading to decreased accuracy in the AI model's predictions. Which action would best improve the performance and reliability of the AI application in this scenario?

A. Implementing a dedicated, high-bandwidth network link between IoT devices and the data processing system. B. Switching to a batch processing model to reduce the frequency of data transfers. C. Deploying a Content Delivery Network (CDN) to cache data closer to the IoT devices. D. Upgrading the IoT devices to more powerful hardware.

Suggested Answer: A Vote an answer

Real-time AI applications, especially those involving IoT devices, depend on rapid and reliable data ingestion to maintain low latency and high throughput. Intermittent delays and data loss suggest a bottleneck in the network connecting the IoT devices to the processing system. Implementing a dedicated, high-bandwidth network link (e.g., using NVIDIA's InfiniBand or high-speed Ethernet solutions) ensures that data flows seamlessly from distributed IoT devices to the AI cluster, reducing latency and preventing packet loss. This aligns with NVIDIA's focus on high-performance networking for distributed AI, as seen in DGX systems and NVIDIA BlueField DPUs, which offload and accelerate network traffic.
Switching to batch processing (Option B) sacrifices real-time performance, which is critical for this use case, making it unsuitable. A CDN (Option C) is designed for static content delivery, not dynamic IoT data streams, and wouldn't address the core issue of real-time ingestion. Upgrading IoT hardware (Option D) might improve local processing but doesn't solve network-related delays or data loss between devices and the AI system. A robust network infrastructure is the most effective solution here.

by Edgar at Mar 18, 2026, 02:19 AM

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