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HPE Private Cloud AI Solutions Sample Questions:

1. An enterprise architecture team is debating the best method to adapt a general-purpose Large Language Model (LLM) for two different, highly-specialized internal use cases:
1. Use Case A: A customer support chatbot that must provide answers strictly based on a rapidly changing knowledge base of product manuals and technical notes. Verifiability and traceability of the information source are critical.
2. Use Case B: An internal code generation assistant that needs to learn the company's specific coding style, proprietary frameworks, and API usage patterns from a large, static codebase.
Which are the most appropriate strategies for these use cases? (Choose 2.)

A) Use fine-tuning for Use Case B to embed the company-specific coding patterns and styles into the model's behavior.
B) Use Retrieval-Augmented Generation (RAG) for Use Case A to provide up-to-date, verifiable information at inference time.
C) Use both RAG and fine-tuning for both use cases as they are always used together.
D) Use RAG for Use Case B to allow the model to retrieve code snippets from the static codebase.
E) Use fine-tuning for Use Case A to ensure the model deeply learns the product manual content.

2. 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 difficulty of managing GPU cluster utilization for training jobs.
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 high cost of NVIDIA AI Enterprise software licenses.

3. An architect has used the HPE Intelligent Configurator and determined that a "Medium - Standard" configuration is required.
When creating the final quote in One Config Advanced (OCA), what is the mandatory prerequisite that the customer is responsible for providing for the solution to be valid?

A) A valid, bring-your-own-license (BYOL) for VMware vSphere Foundation (VVF) or VMware Cloud Foundation (VCF).
B) A rack elevation diagram for the data center.
C) A subscription to the NVIDIA NGC catalog for downloading AI models.
D) A list of all end-users who will access the system.

4. A customer is considering the HPE Private Cloud AI solution. They need to run a moderately sized RAG application for 150 users. They do not have any fine-tuning requirements.
Why would an architect recommend a "Medium" configuration over a "Large" configuration for this customer?

A) The Medium configuration has more storage capacity than the Large configuration.
B) The Medium configuration is the only one that includes the HPE AI Essentials software.
C) The L40S GPUs in the Medium configuration are more cost-effective and power-efficient for this specific inference-heavy workload.
D) The Large configuration does not support Retrieval-Augmented Generation (RAG).

5. 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) 4x HPE ProLiant DL380a Gen11 servers with a total of 16x NVIDIA H100 NVL GPUs
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) 3x HPE ProLiant DL325 Gen11 servers for management

Solutions: