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| Section | Objectives |
|---|---|
| HPE Private Cloud AI Fundamentals | - Overview of private cloud AI concepts - Core AI workload characteristics |
| AI Infrastructure Design | - Networking for AI workloads - Storage and data pipeline design - Compute and GPU considerations |
| Data Management and Governance | - Data lifecycle management - Data governance and compliance |
| Security in Private Cloud AI | - Workload and data protection - Identity and access management |
| HPE GreenLake for AI Solutions | - GreenLake architecture and services - Consumption-based IT model for AI |
| Deployment and Operations | - Monitoring and optimization - Deployment models for AI solutions - Lifecycle management of AI infrastructure |
>> New HPE2-B08 Exam Topics <<
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NEW QUESTION # 57
A customer is planning to deploy an HPE Private Cloud AI solution. Their IT department has provided a worksheet detailing the workload requirements. The solution architect needs to select the appropriate configuration size.
Review the customer's requirements:
```
- Primary Workload: Fine-tuning a 70-billion parameter foundation model
- Secondary Workload: AI Inferencing with RAG
- User Base: 50 developers during tuning; 300 concurrent users for inference
- Data Sensitivity: High (must remain on-premises)
- Power/Cooling: Standard data center air cooling available
```
Which HPE Private Cloud AI configuration is required to meet these demands, and what is the key component that justifies this choice? (Choose 2.)
Answer: B,E
NEW QUESTION # 58
A hospital is developing an AI application to automatically detect specific anomalies in medical images like X-rays and MRIs. The task requires the model to learn and identify complex spatial patterns, such as the shapes and textures of tissues and potential tumors.
Which type of neural network architecture is specifically designed for and best suited to this kind of image analysis task? (Select all that apply.)
Answer: A,B,D
NEW QUESTION # 59
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.)
Answer: B,E
NEW QUESTION # 60
The three pre-defined sizes (Small, Medium, Large) of HPE Private Cloud AI are designed to address different primary workloads. Match the configuration size to its intended primary workload.
*Configuration Size:
1. Small
2. Medium
3. Large
*Primary Workload:
a. AI Inferencing with RAG and large-scale Fine-Tuning
b. AI Inferencing
c. AI Inferencing with RAG
Answer: A
NEW QUESTION # 61
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.)
Answer: B,D
NEW QUESTION # 62
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