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HPE Private Cloud AI Solutions Sample Questions:

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

2. A customer needs a solution for their deployed customer service chatbot. They state: "We don't need to change the model itself, but we need the chatbot to answer questions using our product documentation, which is updated every night. The answers must be fast and based on the latest documents." How would you categorize this workload?

A) A classic AI inferencing workload.
B) A RAG (Retrieval-Augmented Generation) inferencing workload.
C) A large-scale model training workload.
D) A model development and experimentation workload.

3. A customer wants to deploy a turnkey private cloud for a variety of generative AI workloads, including RAG-based chatbots and some model fine-tuning. One of their key IT stakeholders is the data engineer.
Which specific challenge for a data engineer is directly addressed by the HPE Data Fabric component within HPE Private Cloud AI?

A) The high cost of NVIDIA AI Enterprise software licenses.
B) The effort required to create and manage data pipelines and unify diverse, siloed data sources (files, objects, tables) into a single accessible platform.
C) The complexity of writing Python code in a Jupyter Notebook.
D) The difficulty of managing GPU cluster utilization for training jobs.

4. An architect is sizing an HPE Private Cloud AI solution. The customer plans to deploy a generative AI application for 150 concurrent users that requires Retrieval-Augmented Generation (RAG).
The architect enters the following into the HPE Intelligent Configurator:
```
- Use case: Text Generation
- Number of users: 100-250
- RAG: Yes
- Model: Llama 2 13B (tool default for this use case)
```
Based on the provided inputs, which HPE Private Cloud AI configuration will the HPE Intelligent Configurator most likely recommend?

A) Medium - Expanded (4-node)
B) Small - Expanded (2-node)
C) Small - Standard (1-node)
D) Large - Standard (4-node)

5. The three pre-defined sizes (Small, Medium, Large) of HPE Private Cloud AI are designed to address different primary workloads. Match the configuration size to its intended primary workload.
*Configuration Size:
1. Small
2. Medium
3. Large
*Primary Workload:
a. AI Inferencing with RAG and large-scale Fine-Tuning
b. AI Inferencing
c. AI Inferencing with RAG

A) 1-b, 2-a, 3-c
B) 1-a, 2-b, 3-c
C) 1-c, 2-a, 3-b
D) 1-b, 2-c, 3-a

Solutions: