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HPE Private Cloud AI Solutions Sample Questions:

1. An architect is presenting to a customer who is an 'Early AI User'. The customer is unsure about the differences between their two main project ideas.
Project 1: Create an internal chatbot that can answer HR policy questions by accessing the live employee handbook stored on a shared drive.
Project 2: Teach a general-purpose chatbot to adopt the company's formal communication style and tone for drafting official press releases.
How should the architect categorize the primary AI task for each project? (Choose 2.)

A) Project 2 is a classic inferencing workload with no model customization.
B) Project 2 is a fine-tuning workload.
C) Project 1 is a model training workload.
D) Project 1 is a RAG (Retrieval-Augmented Generation) workload.

2. What is the primary purpose of using the "Private Cloud Smart Template" within HPE One Config Advanced (OCA) when quoting an HPE Private Cloud AI solution?

A) To allow for complete customization of every component, including unsupported hardware.
B) To ensure a fast, easy, and validated process for generating a complete and accurate Bill of Materials (BOM) for a pre-integrated solution.
C) To provide a free trial license for the VMware and NVIDIA software.
D) To automatically generate a network diagram and rack elevation for the customer.

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

4. An organization is deploying a multi-tenant AI environment using HPE Private Cloud AI. They need to run several smaller, independent AI inference workloads on a single, powerful NVIDIA H100 GPU to maximize resource utilization. Each workload must be securely isolated with its own dedicated portion of the GPU's compute and memory resources.
What key NVIDIA technology, supported on the Hopper architecture, allows for this secure partitioning of a single physical GPU? (Select all that apply.)

A) Confidential Computing
B) GPUDirect Storage (GDS)
C) Multi-Instance GPU (MIG)
D) NVLink Bridge
E) Remote Direct Memory Access (RDMA)

5. A customer in the public sector wants to use AI to analyze live video feeds from city-wide cameras to automate public safety tasks like detecting traffic accidents or identifying security threats in real-time.
This is their first major AI initiative.
Which AI use case does this scenario represent?

A) Recommender Systems
B) Natural Language Processing (NLP)
C) Drug Discovery
D) Computer Vision / Intelligent Video Analytics

Solutions: