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Network Appliance NetApp Certified AI Expert Sample Questions:

1. Which storage protocols are commonly used for handling large-scale AI data? (Choose two)

A) POSIX-based file systems
B) Object-based storage
C) Parallel file systems
D) File-based systems

2. What is the primary reason for implementing a hybrid cloud architecture in this medical imaging scenario?

A) To simplify network management by using a single, global virtual network spanning the on- premises and cloud environments.
B) To leverage the powerful, elastic GPU compute resources available in the public cloud for model training while keeping sensitive source data on-premises to meet security and HIPAA compliance requirements.
C) To exclusively use cloud-native AI services, eliminating the need for any on-premises hardware.
D) To reduce the overall cost of storage by keeping all data in the public cloud.

3. Which of the following techniques are used to maximize GPU utilization in AI workloads? (Choose two)

A) Balancing compute and storage workloads efficiently
B) Utilizing CPU-based workloads for all tasks
C) Using larger batch sizes
D) Scheduling GPU-intensive tasks during off-peak hours

4. What is the primary architectural advantage of using a NetApp AIPod with NVIDIA DGX servers for the AI training cluster, as described in the scenario?

A) It exclusively uses object storage, which simplifies access for data scientists using S3-native tools.
B) It prioritizes CPU performance over GPU performance for traditional machine learning algorithms.
C) It is a reference architecture that is pre-validated by NetApp and NVIDIA to eliminate design complexity and ensure predictable performance for AI workloads.
D) It is designed for small-scale, departmental AI projects and cannot be scaled.

5. Given the company's goal of combining physics-based simulations with AI-driven analytics on a shared data foundation, which industry trend does this project best represent?

A) The replacement of all physical testing with digital simulations.
B) The separation of AI and HPC into dedicated, air-gapped environments.
C) The convergence of AI, High-Performance Computing (HPC), and analytics on a unified data infrastructure.
D) The exclusive use of public cloud resources for all computational tasks.

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