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HPE Private Cloud AI Solutions Sample Questions:

1. A customer needs a solution for AI inferencing at the edge for a computer vision application. They have determined a Small configuration of HPE Private Cloud AI is sufficient. The solution also requires several value-added services, including an AI transformation workshop and a data design service.
How should an architect attach these services in One Config Advanced (OCA)?

A) The services must be quoted separately from the hardware and software configuration.
B) The services are automatically included in the Smart Template and require no action.
C) The architect must open a support ticket with HPE to have the services added to the quote.
D) The services can be selected and added to the configuration as optional line items within OCA.

2. An architect is designing an infrastructure solution for an AI workload that involves processing massive datasets for training. The goal is to minimize data transfer latency between the storage system and the GPUs in the compute nodes. The architect wants to enable the NVIDIA GPUs to fetch data directly from the NVMe storage array, bypassing the server's CPU and main memory.
Review the proposed architectural components:
```
- Compute Nodes: HPE ProLiant DL380a Gen11 with NVIDIA H100 GPUs
- Storage: HPE GreenLake for File Storage
- Interconnect: Ethernet with RoCE support
```
Which technology must be enabled and properly configured across these components to achieve this direct GPU-to-storage data path? (Choose 2.)

A) Multi-Instance GPU (MIG)
B) NVLink
C) Confidential Computing
D) GPUDirect Storage (GDS)
E) RDMA over Converged Ethernet (RoCE)

3. A company has developed a custom fraud detection model. Their data science team wants to deploy this model into production for other applications to use. They want to avoid the complexity of manually configuring the serving environment, optimizing for hardware, and creating a scalable API endpoint.
How does using an NVIDIA Inference Microservice (NIM) within HPE Private Cloud AI simplify this process?

A) NIM provisions the underlying Kubernetes cluster and physical servers.
B) NIM provides a framework that packages the model into an optimized, ready-to-deploy container with a standard API.
C) NIM automatically fine-tunes the model on new data to improve its accuracy.
D) NIM directly connects to the raw data sources to perform data preparation and cleaning.

4. A large financial institution, a known "Deployer of AI at scale," needs to train a next-generation fraud detection model. This new model has over a trillion parameters, significantly larger than their current models, and requires an exascale-class computing solution to be trained in a reasonable timeframe.
Which HPE AI solution should be positioned to meet this customer's demanding requirement?

A) HPE Cray systems
B) HPE Private Cloud AI with NVIDIA, Large configuration
C) AI-optimized HPE ProLiant DL servers
D) HPE GreenLake for File Storage

5. A customer is building an application to classify images of defective products on a manufacturing line.
Which type of neural network layer is essential for this model to automatically learn and identify visual features like edges, corners, and textures in the images?

A) An output layer with a softmax function
B) A recurrent layer
C) A dense (fully connected) layer
D) A convolutional layer

Solutions: