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HPE Private Cloud AI Solutions Sample Questions:

1. An architect is building a final configuration for an HPE Private Cloud AI solution using One Config Advanced (OCA). After selecting the "HPE Private Cloud AI - Medium Expanded" Smart Template, they review the generated Bill of Materials (BOM).
Which components are characteristic of the Medium Expanded configuration that the architect should expect to see in the OCA-generated BOM? (Select all that apply.)

A) 2x HPE Aruba Networking CX 6300M Switches
B) 16x NVIDIA H100 NVL GPUs
C) 1x HPE ProLiant DL380a Gen11 Server
D) 16x NVIDIA L40S GPUs
E) 4x HPE ProLiant DL380a Gen11 Servers
F) 2x NVIDIA SN4700M Switches

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

3. A customer is planning to deploy an HPE Private Cloud AI solution. Their IT department has provided a worksheet detailing the workload requirements. The solution architect needs to select the appropriate configuration size.
Review the customer's requirements:
```
- Primary Workload: Fine-tuning a 70-billion parameter foundation model
- Secondary Workload: AI Inferencing with RAG
- User Base: 50 developers during tuning; 300 concurrent users for inference
- Data Sensitivity: High (must remain on-premises)
- Power/Cooling: Standard data center air cooling available
```
Which HPE Private Cloud AI configuration is required to meet these demands, and what is the key component that justifies this choice? (Choose 2.)

A) The key component is the HPE ProLiant DL325 server in the management plane.
B) The key component is the NVIDIA L40S GPU, which is optimized for RAG workloads.
C) The key component is the NVIDIA H100 NVL GPU, designed for large-scale training and fine-tuning.
D) The solution requires a Medium configuration.
E) The solution requires a Large configuration.

4. An architect is designing an AI solution to create a medical chatbot that assists doctors by answering questions based on the latest published medical research. The system must be highly reliable, and its answers must be traceable to the source publications. The customer has highlighted that their internal data science team lacks the expertise for complex model retraining but can manage data ingestion pipelines.
Given the customer requirements, which architectural components should the architect include in the solution design? (Select all that apply.)
```
Customer Requirements:
- AI Use Case: Medical Research Q&A Chatbot
- Key Constraint: Information must be current and verifiable.
- Team Skills: Limited AI model training expertise.
- Data Source: Continuously updated database of medical journals.
```

A) A pre-trained, general-purpose Large Language Model (LLM).
B) An edge-optimized server for model deployment in individual hospital rooms.
C) A Retrieval-Augmented Generation (RAG) framework to query the vector database.
D) A vector database to store embeddings of the medical research papers.
E) A data ingestion and embedding pipeline to process and add new research to the vector database.
F) A process for daily fine-tuning of the base LLM on all new research papers.

5. What is the primary advantage of using a Smart Template in OCA for HPE Private Cloud AI versus manually configuring a similar set of hardware?

A) The Smart Template guarantees the lowest possible price for the hardware.
B) The Smart Template provides a 90-day free trial of the entire solution.
C) The Smart Template allows the use of components from other vendors.
D) The Smart Template ensures all necessary and validated components, including specific cables, power cords, and software SKUs, are included correctly.

Solutions: