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HP HPE2-B08 Exam Syllabus Topics:

SectionWeightObjectives
Software Components of HPE Private Cloud AI with NVIDIA20%- Software functions supporting AI operations
- Benefits of HPE and NVIDIA software stack
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%- Using HPE Intelligent Configurator for sizing
- Building configurations via One Config Advanced (OCA)
- Differences between configuration sizes and options
Customer Assessment and Solution Positioning15%- Position appropriate HPE AI solutions
- Assess AI maturity, workload characteristics and use cases

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HPE Private Cloud AI Solutions Sample Questions (Q61-Q66):

NEW QUESTION # 61
An organization is deploying a multi-tenant AI environment using HPE Private Cloud AI. They need to run several smaller, independent AI inference workloads on a single, powerful NVIDIA H100 GPU to maximize resource utilization. Each workload must be securely isolated with its own dedicated portion of the GPU's compute and memory resources.
What key NVIDIA technology, supported on the Hopper architecture, allows for this secure partitioning of a single physical GPU? (Select all that apply.)

Answer: C,D


NEW QUESTION # 62
An architect is working with a customer who has been identified as an 'AI Pro'. They have a mature AI practice and are looking to scale their efforts in creating 'digital twin' simulations for automotive prototypes. This involves complex, graphics-intensive AI workloads. The customer wants a full-stack, turnkey private cloud solution to accelerate this initiative.
What is the most appropriate HPE solution to position for this customer?

Answer: D


NEW QUESTION # 63
An architect has generated a configuration for HPE Private Cloud AI in OCA. The customer wants to know if they can use their existing data center network switches for the high-performance AI interconnect instead of the NVIDIA Spectrum switches included in the BOM.
What is the correct response?

Answer: B


NEW QUESTION # 64
A data science team has trained a deep learning model for image classification. While the model achieves 99.8% accuracy on the training dataset, its accuracy drops to only 75% on a new, unseen validation dataset.
The team provides the following training metrics:
```
- Training Epochs: 500
- Training Dataset Size: 1,000 images
- Model Parameters: 15 million
- Training Accuracy: 99.8%
- Validation Accuracy: 75.3%
```
What is the most likely cause of this performance discrepancy?

Answer: A


NEW QUESTION # 65
A data science team is struggling to manage their AI/ML projects. They use a variety of open-source tools for data preparation, training, and MLOps, but integrating them is complex and time-consuming.
They need a unified platform that provides self-service access to a curated and pre-integrated set of these tools.
Which HPE Private Cloud AI software component is specifically designed to solve this problem?

Answer: C


NEW QUESTION # 66
......

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