HP Hybrid Cloud HPE2-B08

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HP Hybrid Cloud HPE2-B08 HPE Private Cloud AI Solutions Exams

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HP HPE2-B08 Exam Syllabus Topics:

HPE Private Cloud AI Solutions Sample Questions:

1. A customer needs a solution for AI inferencing at the edge for a computer vision application. They have determined a Small configuration of HPE Private Cloud AI is sufficient. The solution also requires several value-added services, including an AI transformation workshop and a data design service.
How should an architect attach these services in One Config Advanced (OCA)?

A) The architect must open a support ticket with HPE to have the services added to the quote.
B) The services must be quoted separately from the hardware and software configuration.
C) The services can be selected and added to the configuration as optional line items within OCA.
D) The services are automatically included in the Smart Template and require no action.

2. What is the primary architectural advantage of the NVIDIA Grace Hopper Superchip (e.g., GH200) for large-scale AI workloads?

A) It replaces the need for server memory (DRAM) by using the GPU's global memory exclusively.
B) It uses on-chip encryption to create a confidential computing environment for the CPU.
C) It is the first NVIDIA GPU to feature fourth-generation Tensor Cores for enhanced matrix calculations.
D) It combines a CPU and a GPU on a single superchip, connected by a high-speed, low-latency NVLink-C2C interconnect.

3. 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
```

A) Recommend that the customer build their own solution from individual components to have maximum control.
B) Use HPE AI Essentials to manage the training cluster, providing features like experiment tracking and optimized resource scheduling for the fine-tuning job.
C) Implement a Retrieval-Augmented Generation (RAG) architecture for the customer service chatbot to ensure it uses the latest, hourly-updated information.
D) Position Al-optimized HPE ProLiant DL servers at the edge for the fine-tuning workload to reduce data transfer costs.
E) Rely solely on public cloud services for the fine-tuning job to avoid capital expenditure on high- performance GPUs.
F) Use the HPE Private Cloud AI Large configuration with NVIDIA H100 GPUs to provide the necessary performance for the large-scale fine-tuning task.

4. 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?

A) NIM automatically fine-tunes the model on new data to improve its accuracy.
B) NIM provisions the underlying Kubernetes cluster and physical servers.
C) NIM directly connects to the raw data sources to perform data preparation and cleaning.
D) NIM provides a framework that packages the model into an optimized, ready-to-deploy container with a standard API.

5. 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.)

A) NeMo Retriever
B) NeMo Curator
C) NeMo Evaluator
D) NeMo Customizer
E) NeMo Guardrails

Solutions: