HPE2-B08 Übungsmaterialien - HPE2-B08 Lernressourcen & HPE2-B08 Prüfungsfragen

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HP HPE2-B08 Exam Syllabus Topics:

Section	Weight	Objectives
Managing and Operating HPE Private Cloud AI Solutions	30%	- Identify how to manage storage and data resources - Identify troubleshooting procedures and common issues - Explain backup and recovery procedures - Describe the tools and methods for managing HPE Private Cloud AI - Describe how to manage users and access control - Explain how to monitor HPE Private Cloud AI performance and health
Supporting HPE Private Cloud AI Solutions	20%	- Identify how to perform firmware and software updates - Describe support resources and documentation - Explain how to work with HPE support services - Describe capacity planning and optimization best practices
Architecting HPE Private Cloud AI Solutions	20%	- Explain the HPE Private Cloud AI sizing and configuration guidelines - Describe the AI/ML lifecycle and data pipeline requirements - Explain common AI use cases and how they map to workloads - Identify components of the HPE Private Cloud AI architecture - Describe how HPE Private Cloud AI supports AI/ML workloads
Installing and Configuring HPE Private Cloud AI Solutions	30%	- Identify how to access and use HPE Private Cloud AI management interfaces - Describe how to validate the HPE Private Cloud AI installation - Identify the steps to configure the HPE Private Cloud AI environment - Describe the prerequisites for installing HPE Private Cloud AI - Explain how to deploy and configure HPE Private Cloud AI components

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HPE Private Cloud AI Solutions HPE2-B08 Prüfungsfragen mit Lösungen (Q24-Q29):

24. Frage
A customer needs to run a generative AI workload at multiple, dispersed edge locations. Each location has significant space and power constraints. The workload is inference-only and does not require the absolute highest performance, but rather a balance of good performance and energy efficiency.
Which HPE ProLiant server and NVIDIA GPU combination is specifically positioned for this type of edge AI use case?

A. HPE ProLiant DL384 Gen12 server with NVIDIA H200 NVL GPUs
B. HPE Cray system with NVIDIA Grace Hopper Superchips
C. HPE ProLiant DL320 Gen11 server with NVIDIA L4 GPUs
D. HPE ProLiant DL380a server with NVIDIA H100 NVL GPUs

Antwort: C

25. Frage
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?

A. Convolutional Neural Network (CNN)
B. A fully connected, feedforward neural network
C. Transformer model
D. K-Means Clustering Algorithm

Antwort: C

26. Frage
A customer is building an application to classify images of defective products on a manufacturing line.
Which type of neural network layer is essential for this model to automatically learn and identify visual features like edges, corners, and textures in the images?

A. A convolutional layer
B. An output layer with a softmax function
C. A recurrent layer
D. A dense (fully connected) layer

Antwort: A

27. Frage
A customer needs a solution for their deployed customer service chatbot. They state: "We don't need to change the model itself, but we need the chatbot to answer questions using our product documentation, which is updated every night. The answers must be fast and based on the latest documents." How would you categorize this workload?

A. A large-scale model training workload.
B. A classic AI inferencing workload.
C. A model development and experimentation workload.
D. A RAG (Retrieval-Augmented Generation) inferencing workload.

Antwort: D

28. Frage
An architect is presenting to a customer who is an 'Early AI User'. The customer is unsure about the differences between their two main project ideas.
Project 1: Create an internal chatbot that can answer HR policy questions by accessing the live employee handbook stored on a shared drive.
Project 2: Teach a general-purpose chatbot to adopt the company's formal communication style and tone for drafting official press releases.
How should the architect categorize the primary AI task for each project? (Choose 2.)

A. Project 2 is a classic inferencing workload with no model customization.
B. Project 2 is a fine-tuning workload.
C. Project 1 is a model training workload.
D. Project 1 is a RAG (Retrieval-Augmented Generation) workload.

Antwort: B,D

29. Frage
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