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| Section | Weight | Objectives |
|---|---|---|
| Architecting HPE Private Cloud AI Solutions | 20% | - Explain the HPE Private Cloud AI sizing and configuration guidelines - Describe how HPE Private Cloud AI supports AI/ML workloads - Explain common AI use cases and how they map to workloads - Describe the AI/ML lifecycle and data pipeline requirements - Identify components of the HPE Private Cloud AI architecture |
| Supporting HPE Private Cloud AI Solutions | 20% | - Describe capacity planning and optimization best practices - Identify how to perform firmware and software updates - Explain how to work with HPE support services - Describe support resources and documentation |
| Managing and Operating HPE Private Cloud AI Solutions | 30% | - Explain backup and recovery procedures - 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 - Describe the tools and methods for managing HPE Private Cloud AI |
| Installing and Configuring HPE Private Cloud AI Solutions | 30% | - Describe how to validate the HPE Private Cloud AI installation - Explain how to deploy and configure HPE Private Cloud AI components - Identify how to access and use HPE Private Cloud AI management interfaces - Describe the prerequisites for installing HPE Private Cloud AI - Identify the steps to configure the HPE Private Cloud AI environment |
>> Sample HP HPE2-B08 Questions Answers <<
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NEW QUESTION # 18
An architect is meeting with a prospective customer to determine the right HPE AI solution. The customer provides the following information about their situation.
```
- AI Status: No formal AI strategy. One successful PoC for theft prevention using computer vision is running at a single store.
- Goal: Wants to explore creating a "digital twin" of their supply chain for simulation, but has no clear KPIs.
- Team: Two data scientists, one ML engineer.
- Infrastructure: Ad-hoc use of public cloud for the PoC; no standardized tech stack.
```
Based on this profile, which AI maturity level and corresponding HPE solution should the architect initially position? (Choose 2.)
Answer: A,B
NEW QUESTION # 19
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 # 20
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?
Answer: B
NEW QUESTION # 21
An enterprise architecture team is debating the best method to adapt a general-purpose Large Language Model (LLM) for two different, highly-specialized internal use cases:
1. Use Case A: A customer support chatbot that must provide answers strictly based on a rapidly changing knowledge base of product manuals and technical notes. Verifiability and traceability of the information source are critical.
2. Use Case B: An internal code generation assistant that needs to learn the company's specific coding style, proprietary frameworks, and API usage patterns from a large, static codebase.
Which are the most appropriate strategies for these use cases? (Choose 2.)
Answer: C,E
NEW QUESTION # 22
An enterprise wants to build an internal AI platform that functions like an "App Store." Their goal is to provide various internal development teams with a catalog of curated AI models that they can easily deploy and integrate into their applications without needing deep AI expertise. The platform must be secure, reliable, and scalable.
Which software components within the HPE Private Cloud AI stack are essential to building this platform? (Select all that apply.)
Answer: A,B,C,E
NEW QUESTION # 23
......
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