HP HPE2-B08 Exam Questions : HPE Private Cloud AI Solutions

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HP HPE2-B08 Exam Syllabus Topics:

HPE Private Cloud AI Solutions Sample Questions:

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

2. A hospital is developing an AI application to automatically detect specific anomalies in medical images like X-rays and MRIs. The task requires the model to learn and identify complex spatial patterns, such as the shapes and textures of tissues and potential tumors.
Which type of neural network architecture is specifically designed for and best suited to this kind of image analysis task? (Select all that apply.)

A) A Convolutional Neural Network (CNN)
B) A model architecture that includes pooling layers to reduce spatial dimensions
C) A basic, fully connected Artificial Neural Network (ANN)
D) A model architecture that includes convolutional layers for feature extraction
E) A transformer-based model designed for Natural Language Processing (NLP)

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

A) To guarantee packet delivery over lossy internet connections using the TCP protocol.
B) To allow direct memory-to-memory data transfers between nodes, bypassing the CPU kernel and reducing latency.
C) To partition a single physical network adapter into multiple virtual adapters for different tenants.
D) To encrypt data in transit between compute nodes and storage.

4. A customer's distributed AI training job is experiencing poor performance. An analysis reveals high network latency. The architect suspects a misconfiguration in the NVIDIA Spectrum switches that form the RoCE-based AI fabric.
They review the following configuration snippet from one of the switch ports connected to a compute node:
```
interface ethernet 1/1
description "Connection to PCAI-Node-1"
speed 200G
mtu 9216
switchport mode trunk
## Priority Flow Control (PFC) is disabled on this port
```
What is the most likely cause of the performance issue?

A) Priority Flow Control (PFC) is disabled, which is mandatory for a lossless RoCE fabric.
B) The port speed is not sufficient for the connected H100 GPU.
C) The port is incorrectly configured in trunk mode instead of access mode.
D) The MTU size is too small for AI workloads.

5. A retail customer wants to implement an AI-powered recommender system to personalize product suggestions on their e-commerce website. They are an 'Early AI user' and need a full-stack solution that simplifies deployment and management.
Which HPE AI solution is most appropriate for this use case?

A) AI-optimized HPE ProLiant DL servers deployed individually
B) HPE AI Services - Transformation Workshop
C) HPE Cray systems
D) HPE Private Cloud AI with NVIDIA

Solutions: