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Actual exam question for NVIDIA's NCA-AIIO exam Question #: 23 Topic #: 1
A financial services company is developing a machine learning model to detect fraudulent transactions in real- time. They need to manage the entire AI lifecycle, from data preprocessing to model deployment and monitoring. Which combination of NVIDIA software components should they integrate to ensure an efficient and scalable AI development and deployment process?
The AI lifecycle for real-time fraud detection needs efficient data preprocessing, model optimization, and deployment. NVIDIA RAPIDS accelerates data processing on GPUs, TensorRToptimizes models for low- latency inference, and Triton Inference Server scales deployment across platforms-perfect for financial use cases in NVIDIA DGX or cloud environments. Clara (Option A) is healthcare-focused, not fraud. DeepStream (Option C) is video-centric, and CUDA isn't a full training solution. Metropolis (Option D) targets smart cities, and DIGITS is outdated. Option B aligns with NVIDIA's lifecycle strategy.
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