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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Installing and Configuring HPE Private Cloud AI Solutions | 30% | - Describe how to validate the HPE Private Cloud AI installation - 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 - Explain how to deploy and configure HPE Private Cloud AI components |
| Topic 2: Managing and Operating HPE Private Cloud AI Solutions | 30% | - Identify how to manage storage and data resources - Describe the tools and methods for managing HPE Private Cloud AI - Identify troubleshooting procedures and common issues - Explain backup and recovery procedures - Describe how to manage users and access control - Explain how to monitor HPE Private Cloud AI performance and health |
| Topic 3: Architecting HPE Private Cloud AI Solutions | 20% | - Explain common AI use cases and how they map to workloads - Describe how HPE Private Cloud AI supports AI/ML workloads - Describe the AI/ML lifecycle and data pipeline requirements - Identify components of the HPE Private Cloud AI architecture - Explain the HPE Private Cloud AI sizing and configuration guidelines |
| Topic 4: Supporting HPE Private Cloud AI Solutions | 20% | - Describe capacity planning and optimization best practices - Explain how to work with HPE support services - Identify how to perform firmware and software updates - Describe support resources and documentation |
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NEW QUESTION # 82
A company has developed a custom fraud detection model. Their data science team wants to deploy this model into production for other applications to use. They want to avoid the complexity of manually configuring the serving environment, optimizing for hardware, and creating a scalable API endpoint.
How does using an NVIDIA Inference Microservice (NIM) within HPE Private Cloud AI simplify this process?
Answer: A
NEW QUESTION # 83
An architect is sizing an HPE Private Cloud AI solution. The customer plans to deploy a generative AI application for 150 concurrent users that requires Retrieval-Augmented Generation (RAG).
The architect enters the following into the HPE Intelligent Configurator:
```
- Use case: Text Generation
- Number of users: 100-250
- RAG: Yes
- Model: Llama 2 13B (tool default for this use case)
```
Based on the provided inputs, which HPE Private Cloud AI configuration will the HPE Intelligent Configurator most likely recommend?
Answer: B
NEW QUESTION # 84
An AI application is being developed to analyze financial time-series data to predict stock market trends. The model needs to understand long-term dependencies and the sequence in which data points occur.
Which neural network architecture is specifically designed to handle sequential data like text or time- series?
Answer: A
NEW QUESTION # 85
A customer needs a solution for two primary workloads: large-scale model training and real-time inference. They have a team of data scientists who are constantly developing new models and a separate operations team that deploys and manages these models in production.
Which statement best describes how the different stakeholders would interact with the HPE Private Cloud AI solution?
Answer: B
NEW QUESTION # 86
A customer is considering the HPE Private Cloud AI solution. They need to run a moderately sized RAG application for 150 users. They do not have any fine-tuning requirements.
Why would an architect recommend a "Medium" configuration over a "Large" configuration for this customer?
Answer: A
NEW QUESTION # 87
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