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HP HPE2-B08 Exam Syllabus Topics:

SectionWeightObjectives
Customer Assessment and Solution Positioning15%- Assess AI maturity, workload characteristics and use cases
- Position appropriate HPE AI solutions
Fundamental AI Concepts28%- General AI concepts, applications and workloads
- Impact of AI on industries and infrastructure requirements
Infrastructure Components of HPE Private Cloud AI with NVIDIA20%- Benefits of HPE and NVIDIA integrated infrastructure
- Infrastructure capabilities for AI workload requirements
Solution Sizing and Configuration17%- Differences between configuration sizes and options
- Using HPE Intelligent Configurator for sizing
- Building configurations via One Config Advanced (OCA)
Software Components of HPE Private Cloud AI with NVIDIA20%- Benefits of HPE and NVIDIA software stack
- Software functions supporting AI operations

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HPE Private Cloud AI Solutions Sample Questions (Q19-Q24):

NEW QUESTION # 19
During a discovery call, a customer from a telecommunications company explains their primary goal:
"We need to analyze network traffic patterns in real-time to detect anomalies that could indicate a security threat or a network outage." Which key use case for HPE Private Cloud AI does this represent?

Answer: C


NEW QUESTION # 20
A customer is using the NVIDIA NeMo framework within HPE Private Cloud AI to build a custom generative AI application. They need to fine-tune a foundation model using a proprietary dataset. They also want to ensure the final application does not produce toxic content or veer into off-topic conversations.
Which specific toolkits within the NeMo framework should they use to achieve these two distinct goals?
(Choose 2.)

Answer: A,C


NEW QUESTION # 21
A customer in the media and entertainment industry wants a solution to accelerate the creation of 3D animations and renderings. Their artists need to be able to generate complex visual AI content quickly.
The company has a mature AI practice and requires a powerful, data center-based solution.
Which HPE ProLiant server and NVIDIA GPU combination is purpose-built for these generative visual AI workloads?

Answer: C


NEW QUESTION # 22
A large enterprise is adopting HPE Private Cloud AI and needs to accelerate the development of several generative AI applications. Their data science team wants to leverage pre-trained foundation models from NVIDIA but needs to customize them for specific business tasks like contract summarization and internal policy Q&A.
Which NVIDIA AI Enterprise software framework provides a comprehensive, end-to-end toolkit for curating data, customizing models using techniques like PEFT, and implementing guardrails for safe deployment?
```
Customer Goal:
- Accelerate development of custom generative AI apps
- Utilize pre-trained foundation models
- Require tools for data prep, model customization, and safety
```

Answer: A


NEW QUESTION # 23
A global logistics company is designing an enterprise-grade AI solution. The project has two main goals:
1. Goal 1: Develop a highly accurate, proprietary logistics optimization model by fine-tuning a foundation model on the company's massive, confidential shipping dataset (20TB). This requires a secure, high- performance, multi-node training environment.
2. Goal 2: Deploy a generative AI-powered chatbot for the customer service department. The chatbot must provide real-time shipment status and answer policy questions based on a knowledge base that is updated hourly.
The company is classified as an 'AI Pro,' with a formal AI strategy and a Center of Excellence, but they want a turnkey solution to accelerate time-to-market.
Which components and strategies should the architect propose to meet all the customer's requirements?
(Select all that apply.)
```
Customer Profile:
- Industry: Global Logistics
- AI Maturity: AI Pro
- Key Workloads: Large-scale Fine-Tuning, Real-time RAG
- Desired Solution: Turnkey, enterprise-grade private cloud
```

Answer: A,C,D


NEW QUESTION # 24
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