HPE2-B08 Test Review - Latest HPE2-B08 Test Answers
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Latest HP HPE2-B08 Test Answers - HPE2-B08 Discount Code
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HPE Private Cloud AI Solutions Sample Questions (Q58-Q63):
NEW QUESTION # 58
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. Retrain the model from scratch using a much larger and more diverse public dataset.
- B. Apply stricter content moderation and safety guardrails to the model's output.
- C. Implement a Retrieval-Augmented Generation (RAG) framework to provide the model with verifiable, external context at inference time.
- D. Increase the number of hidden layers in the model's architecture.
- E. Reduce the "temperature" setting during inference to make the model's output less random and more focused.
Answer: C,E
NEW QUESTION # 59
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.)
- A. Multi-Instance GPU (MIG)
- B. NVLink
- C. GPUDirect Storage (GDS)
- D. RDMA over Converged Ethernet (RoCE)
- E. Confidential Computing
Answer: C,D
NEW QUESTION # 60
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-a, 2-b, 3-c
- C. 1-b, 2-a, 3-c
- D. 1-b, 2-c, 3-a
Answer: D
NEW QUESTION # 61
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 1 is a RAG (Retrieval-Augmented Generation) workload.
- B. Project 1 is a model training workload.
- C. Project 2 is a classic inferencing workload with no model customization.
- D. Project 2 is a fine-tuning workload.
Answer: A,D
NEW QUESTION # 62
An architect is working with a customer who has been identified as an 'AI Pro'. They have a mature AI practice and are looking to scale their efforts in creating 'digital twin' simulations for automotive prototypes. This involves complex, graphics-intensive AI workloads. The customer wants a full-stack, turnkey private cloud solution to accelerate this initiative.
What is the most appropriate HPE solution to position for this customer?
- A. A custom solution built on individual HPE ProLiant servers.
- B. A set of AI-optimized HPE ProLiant DL servers for edge deployment.
- C. HPE Private Cloud AI with NVIDIA.
- D. An HPE AI Services - Transformation Workshop to redefine their goals.
Answer: C
NEW QUESTION # 63
......
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