Q33. A customer is expanding their HPE Private Cloud AI “Medium” configuration to support a new generative AI inferencing workload. They are concerned about network congestion and latency, as the AI workload is known to generate large, sudden bursts of traffic between the compute nodes and the storage system.
The solution uses NVIDIA Spectrum SN4700M switches for the AI interconnect.
Which feature of these switches is specifically designed to handle bursty traffic and prevent packet loss in a lossless Ethernet fabric?

Q34. A customer states they need an AI solution for a “summarization” use case that will be accessed by approximately 75 concurrent users. The underlying data is updated frequently, so RAG will be required.
When using the HPE Intelligent Configurator, which three inputs are mandatory to get an initial sizing recommendation?

Q35. An architect is designing an infrastructure solution for an AI workload that involves processing massive datasets for training. The goal is to minimize data transfer latency between the storage system and the GPUs in the compute nodes. The architect wants to enable the NVIDIA GPUs to fetch data directly from the NVMe storage array, bypassing the server’s CPU and main memory.
Review the proposed architectural components:
“`
– Compute Nodes: HPE ProLiant DL380a Gen11 with NVIDIA H100 GPUs
– Storage: HPE GreenLake for File Storage
– Interconnect: Ethernet with RoCE support
“`
Which technology must be enabled and properly configured across these components to achieve this direct GPU-to-storage data path? (Choose 2.)

Q36. 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.)

Q37. A customer has used the HPE Intelligent Configurator and determined that the HPE Private Cloud AI
“Small – Expanded” configuration meets their needs. They now need to generate a final, quotable Bill of Materials (BOM).
What is the most direct and efficient method for the sales team to create this BOM?

Q38. An architect is explaining the structure of a simple Artificial Neural Network (ANN) to a client.
Review the following diagram of the network:
“`
Input Layer Hidden Layer Output Layer
(Node) — (Node) — (Node)
(Node) / (Node) — (Node)
(Node) –/ (Node) / (Node)
“`
Which component of the network is responsible for producing the final prediction, such as classifying an image as either a “cat” or a “dog”?

Q39. 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.)

Q40. After an architect selects the “HPE Private Cloud AI – Large – Expanded” Smart Template in OCA, they see it includes a significant number of “HPE Factory Express Complex Unit of SVC” services.
What is the purpose of these bundled services?

Q41. 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?

Q42. An enterprise is designing a solution for training a large, custom Convolutional Neural Network (CNN) for a new computer vision application. Their data science team has determined that the training process will need to be distributed across multiple GPUs to be completed in a reasonable timeframe. The training process involves intensive matrix multiplication operations.
The architect is specifying components from the HPE Private Cloud AI solution.
Which infrastructure components are critical for accelerating this specific distributed training workload?
(Select all that apply.)
“`
Workload Analysis:
– AI Model: Large Convolutional Neural Network (CNN)
– Task: Distributed Training
– Key Operation: Intensive matrix multiplication
“`

Q43. 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?

Q44. An architect is comparing two different models for a text summarization task.
Model A: A Convolutional Neural Network (CNN)
*Model B: A Transformer-based model
Why is the Transformer-based model (Model B) fundamentally better suited for this task?

Q45. A customer wants a single platform to handle the following workloads:
* Real-time fraud detection using a trained model (Inference).
* A chatbot for internal support that uses a corporate knowledge base (RAG).
* Quarterly updates to their custom logistics model (Fine-tuning).
The customer is an ‘AI Pro’ looking for a turnkey, on-premises cloud experience.
Which HPE solution is designed to handle this mix of inference, RAG, and fine-tuning workloads?

Q46. An architect is selecting the appropriate HPE Private Cloud AI configuration for a customer. The customer’s primary workload is fine-tuning a 70B parameter model, a task that is extremely sensitive to compute latency and requires the highest possible performance for multi-node distributed training.
Which specific infrastructure components included in the “Large” configuration of HPE Private Cloud AI are essential for meeting this high-performance training requirement? (Select all that apply.)

Q47. A sales professional is preparing a quote for an HPE Private Cloud AI solution in OCA and needs to ensure the correct support services are attached.
What is the default level of support included with all components when using the “Flexible services” option in the Smart Template?

Q48. 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

Q49. 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.)

Q50. An organization is using HPE Private Cloud AI to manage a large, multi-tenant Kubernetes environment for its data science teams. They need to ensure that data access is securely managed and that each team’s data is isolated within a logical, policy-driven boundary. Additionally, they need to store and access data from multiple sources, including NFS clients and S3-compatible object stores.
Which software components of the HPE Private Cloud AI stack work together to provide this unified, policy-driven, multi-protocol data access? (Select all that apply.)

Q51. A company is implementing a RAG-based chatbot using HPE Private Cloud AI. To ensure the chatbot provides safe and appropriate responses, the development team needs to implement guardrails to prevent it from discussing off-topic subjects and to block it from using harmful language.
Which specific toolkit within the NVIDIA NeMo framework is designed for this purpose?
“`
NVIDIA NeMo Framework Components:
1. NeMo Curator
2. NeMo Customizer
3. NeMo Evaluator
4. NeMo Retriever
5. NeMo Guardrails
“`

Q52. 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?

Q53. An architect is positioning an HPE Private Cloud AI solution to a customer who is an “AI Pro.” The customer’s CIO is the key decision maker.
Which benefits of the solution would be most compelling to this stakeholder? (Choose 2.)

Q54. What is the primary purpose of using RDMA over Converged Ethernet (RoCE) in the AI interconnect fabric of an HPE Private Cloud AI solution?

Q55. A customer needs a solution for two primary workloads: large-scale model training and real-time inference. They have a team of data scientists who are constantly developing new models and a separate operations team that deploys and manages these models in production.
Which statement best describes how the different stakeholders would interact with the HPE Private Cloud AI solution?

Q56. An architect is designing a high-performance computing environment for a customer with two distinct, demanding workloads:
1. A large-scale, multi-node deep learning model that requires the fastest possible server-to-server communication.
2. A data-intensive analytics workload that requires the fastest possible data ingestion from an HPE GreenLake for File Storage array.
Which combination of technologies from the HPE Private Cloud AI solution should the architect select to optimize both workloads? (Select all that apply.)