HP : HPE2-B08 Questions & Answers

HP HPE2-B08 Exam Syllabus Topics:

HPE Private Cloud AI Solutions Sample Questions:

1. 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?

A) Integrated Silicon Root of Trust to validate the switch firmware integrity.
B) Support for Fibre Channel over Ethernet (FCoE) encapsulation.
C) The ability to route traffic based on application-layer metadata.
D) A fully shared buffer architecture that can dynamically absorb traffic bursts from any port.

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

3. A development team reports that their custom-trained Large Language Model (LLM) is "hallucinating"
- generating factually incorrect or nonsensical information, especially when asked questions outside the scope of its training data. The model was created by fine-tuning a foundation model on a large but static internal dataset. The team wants to improve the model's factual accuracy and reliability without embarking on a new, large-scale training project.
Which are the most appropriate strategies to mitigate this issue? (Choose 2.)

A) Increase the number of hidden layers in the model's architecture.
B) Retrain the model from scratch using a much larger and more diverse public dataset.
C) Reduce the "temperature" setting during inference to make the model's output less random and more focused.
D) Implement a Retrieval-Augmented Generation (RAG) framework to provide the model with verifiable, external context at inference time.
E) Apply stricter content moderation and safety guardrails to the model's output.

4. 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?

A) HPE Cray systems
B) AI-optimized HPE ProLiant DL servers
C) HPE Private Cloud AI with NVIDIA
D) NVIDIA DGX Systems
E) An HPE AI Services - Transformation Workshop

5. What is the primary function of hidden layers in a deep learning model?

A) To apply weights and transformations to the outputs of preceding layers, allowing the network to learn progressively more complex features.
B) To directly receive the initial, raw input data for the model.
C) To store the complete training dataset for real-time retrieval during inference.
D) To format the final output of the network into a human-readable prediction or classification.

Solutions: