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| Section | Weight | Objectives |
|---|---|---|
| Supporting HPE Private Cloud AI Solutions | 20% | - Describe capacity planning and optimization best practices - Explain how to work with HPE support services - Describe support resources and documentation - Identify how to perform firmware and software updates |
| Installing and Configuring HPE Private Cloud AI Solutions | 30% | - Identify how to access and use HPE Private Cloud AI management interfaces - Describe how to validate the HPE Private Cloud AI installation - Explain how to deploy and configure HPE Private Cloud AI components - Describe the prerequisites for installing HPE Private Cloud AI - Identify the steps to configure the HPE Private Cloud AI environment |
| Managing and Operating HPE Private Cloud AI Solutions | 30% | - Describe how to manage users and access control - Identify troubleshooting procedures and common issues - Explain how to monitor HPE Private Cloud AI performance and health - Identify how to manage storage and data resources - Explain backup and recovery procedures - Describe the tools and methods for managing HPE Private Cloud AI |
| Architecting HPE Private Cloud AI Solutions | 20% | - Describe how HPE Private Cloud AI supports AI/ML workloads - Explain common AI use cases and how they map to workloads - Explain the HPE Private Cloud AI sizing and configuration guidelines - Identify components of the HPE Private Cloud AI architecture - Describe the AI/ML lifecycle and data pipeline requirements |
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NEW QUESTION # 39
In a Natural Language Processing (NLP) task, what is the role of a tokenizer?
Answer: A
NEW QUESTION # 40
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?
Answer: D
NEW QUESTION # 41
An architect is designing a distributed training solution using HPE Private Cloud AI. The solution involves multiple HPE ProLiant DL380a servers, each with four NVIDIA H100 GPUs.
Review the logical network topology:
```
[HPE ProLiant Server 1] \
- GPU 0 <--> GPU 1 (Internal)
- GPU 2 <--> GPU 3 (Internal)
\
[NVIDIA Spectrum Switch (RoCE)] <--> [HPE GreenLake for File Storage]
/
[HPE ProLiant Server 2] /
- GPU 0 <--> GPU 1 (Internal)
- GPU 2 <--> GPU 3 (Internal)
```
Which interconnect technology facilitates the highest-bandwidth communication path labeled "(Internal)" for scaling the training job across the GPUs within a single server?
Answer: D
NEW QUESTION # 42
A customer wants to enhance their existing Large Language Model (LLM) to provide more accurate and contextually relevant answers based on a proprietary, rapidly changing knowledge base of legal documents. They are considering two approaches: fine-tuning and Retrieval-Augmented Generation (RAG).
Review the data flow diagram for the proposed RAG implementation:
```
User Query -> [Query Encoder] -> Vector DB Search -> [Retrieved Documents] --+
|
+-> [LLM Prompt] -> LLM -> Response
```
Based on the diagram and the scenario, which statement accurately identifies a primary advantage of the RAG approach for this customer?
Answer: D
NEW QUESTION # 43
A customer explains that their data engineers are spending too much time managing disparate data pipelines with a complex set of open-source tools. They are an 'Early AI User' trying to standardize their approach.
Which value proposition of HPE Private Cloud AI directly addresses this specific stakeholder's pain point?
Answer: C
NEW QUESTION # 44
......
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