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HPE Private Cloud AI Solutions Sample Questions:

1. A customer who is an "AI Beginner" wants to start an AI inferencing project at their edge locations.
Their goal is to analyze security camera feeds to help prevent theft. They have a limited budget and IT staff at the edge sites.
Which HPE AI solution is the most appropriate to position for this specific scenario?

A) HPE Private Cloud AI with NVIDIA
B) AI-optimized HPE ProLiant DL servers
C) HPE Cray systems
D) An HPE AI Services - Transformation Workshop
E) NVIDIA DGX Systems

2. An architect is working with a customer who has been identified as an 'AI Pro'. They have a mature AI practice and are looking to scale their efforts in creating 'digital twin' simulations for automotive prototypes. This involves complex, graphics-intensive AI workloads. The customer wants a full-stack, turnkey private cloud solution to accelerate this initiative.
What is the most appropriate HPE solution to position for this customer?

A) HPE Private Cloud AI with NVIDIA.
B) An HPE AI Services - Transformation Workshop to redefine their goals.
C) A custom solution built on individual HPE ProLiant servers.
D) A set of AI-optimized HPE ProLiant DL servers for edge deployment.

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

4. An architect is using the HPE One Config Advanced (OCA) Smart Template for "HPE Private Cloud AI
- Small - Standard".
What is the worker node configuration they should expect to see in the generated Bill of Materials (BOM)?

A) 3x HPE ProLiant DL325 Gen11 servers for management
B) 1x HPE ProLiant DL380a Gen11 server with 4x NVIDIA L40S GPUs
C) 2x HPE ProLiant DL380a Gen11 servers with a total of 8x NVIDIA L40S GPUs
D) 4x HPE ProLiant DL380a Gen11 servers with a total of 16x NVIDIA H100 NVL GPUs

5. An 'AI Pro' customer wants to deploy a solution to create 'digital twins' of their manufacturing equipment for predictive maintenance simulations. This workload requires significant GPU power for both the simulation and the underlying AI model.
Which HPE solution should be positioned as the primary platform for this advanced, data-center based workload?

A) Individual HPE ProLiant DL320 Gen11 servers at the edge.
B) HPE Private Cloud AI with NVIDIA.
C) The customer's existing VDI environment.
D) A standard data warehouse solution without GPU acceleration.

Solutions: