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HP HPE2-B08 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Fundamental AI Concepts28%- Impact of AI on industries and infrastructure requirements
- General AI concepts, applications and workloads
Topic 2: Customer Assessment and Solution Positioning15%- Position appropriate HPE AI solutions
- Assess AI maturity, workload characteristics and use cases
Topic 3: Software Components of HPE Private Cloud AI with NVIDIA20%- Software functions supporting AI operations
- Benefits of HPE and NVIDIA software stack
Topic 4: Solution Sizing and Configuration17%- Differences between configuration sizes and options
- Building configurations via One Config Advanced (OCA)
- Using HPE Intelligent Configurator for sizing
Topic 5: Infrastructure Components of HPE Private Cloud AI with NVIDIA20%- Benefits of HPE and NVIDIA integrated infrastructure
- Infrastructure capabilities for AI workload requirements

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HPE Private Cloud AI Solutions Sample Questions (Q48-Q53):

NEW QUESTION # 48
A customer wants a single platform to handle the following workloads:
* Real-time fraud detection using a trained model (Inference).
* A chatbot for internal support that uses a corporate knowledge base (RAG).
* Quarterly updates to their custom logistics model (Fine-tuning).
The customer is an 'AI Pro' looking for a turnkey, on-premises cloud experience.
Which HPE solution is designed to handle this mix of inference, RAG, and fine-tuning workloads?

Answer: B


NEW QUESTION # 49
An IT director for a regional retail chain tells you they are "doing AI." Upon further questioning, you learn they have one data scientist who has built a single, experimental sales forecasting model as a proof-of-concept (PoC). The project lacks clear KPIs for success and there is no formal strategy for how to productionize it or what to do next.
How would you classify this customer's AI maturity level?

Answer: B


NEW QUESTION # 50
A customer has selected the "HPE Private Cloud AI - Medium - Expanded" configuration.
Which of the following resource counts correctly describes this specific configuration?

Answer: C


NEW QUESTION # 51
An architect is assessing a customer's workloads to position the correct HPE Private Cloud AI configuration. The customer has a single, massive task: training a foundational vision model from scratch using a petabyte-scale image dataset. The project is expected to take months and requires the absolute maximum compute performance available.
Which AI workload type does this represent, and which HPE solution is most appropriate?

Answer: D


NEW QUESTION # 52
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: C,D,F


NEW QUESTION # 53
......

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