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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Solution Sizing and Configuration | 17% | - Using HPE Intelligent Configurator for sizing - Building configurations via One Config Advanced (OCA) - Differences between configuration sizes and options |
| Topic 2: Customer Assessment and Solution Positioning | 15% | - Assess AI maturity, workload characteristics and use cases - Position appropriate HPE AI solutions |
| Topic 3: Fundamental AI Concepts | 28% | - Impact of AI on industries and infrastructure requirements - General AI concepts, applications and workloads |
| Topic 4: Software Components of HPE Private Cloud AI with NVIDIA | 20% | - Software functions supporting AI operations - Benefits of HPE and NVIDIA software stack |
| Topic 5: Infrastructure Components of HPE Private Cloud AI with NVIDIA | 20% | - Infrastructure capabilities for AI workload requirements - Benefits of HPE and NVIDIA integrated infrastructure |
>> HPE2-B08 Valid Test Objectives <<
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NEW QUESTION # 13
A customer in the public sector wants to use AI to analyze live video feeds from city-wide cameras to automate public safety tasks like detecting traffic accidents or identifying security threats in real-time.
This is their first major AI initiative.
Which AI use case does this scenario represent?
Answer: A
NEW QUESTION # 14
A financial services firm is building a fraud detection application on HPE Private Cloud AI. The application needs to process a continuous stream of transaction data from multiple sources in real time.
The data science team requires a robust platform to build, manage, and execute the complex data pipelines needed to feed the AI model.
Which pre-integrated open-source tool within HPE AI Essentials is the industry standard for orchestrating and managing these complex data workflows and pipelines?
Answer: D
NEW QUESTION # 15
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 # 16
Match the stakeholder in an AI project to their most likely primary concern.
Stakeholders:
1. Data Scientist
2. AI Decision Maker (CIO)
3. Data Engineer
Concerns:
a. "How can I easily build, manage, and automate data pipelines to feed our models?" b. "What is the total cost of ownership (TCO) and return on investment (ROI) for this AI initiative?" c. "Which hyperparameter tuning method will give my model the highest accuracy?"
Answer: B
NEW QUESTION # 17
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
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Answer: D
NEW QUESTION # 18
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