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| Section | Weight | Objectives |
|---|---|---|
| Fundamental AI Concepts | 28% | - General AI concepts, applications and workloads - Impact of AI on industries and infrastructure requirements |
| Software Components of HPE Private Cloud AI with NVIDIA | 20% | - Software functions supporting AI operations - Benefits of HPE and NVIDIA software stack |
| Solution Sizing and Configuration | 17% | - Using HPE Intelligent Configurator for sizing - Building configurations via One Config Advanced (OCA) - Differences between configuration sizes and options |
| Customer Assessment and Solution Positioning | 15% | - Position appropriate HPE AI solutions - Assess AI maturity, workload characteristics and use cases |
| Infrastructure Components of HPE Private Cloud AI with NVIDIA | 20% | - Benefits of HPE and NVIDIA integrated infrastructure - Infrastructure capabilities for AI workload requirements |
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NEW QUESTION # 43
An architect is assessing a customer's workloads to position the correct HPE Private Cloud AI configuration. The customer has a single, massive task: training a foundational vision model from scratch using a petabyte-scale image dataset. The project is expected to take months and requires the absolute maximum compute performance available.
Which AI workload type does this represent, and which HPE solution is most appropriate?
Answer: C
NEW QUESTION # 44
A customer has used the HPE Intelligent Configurator and determined that the HPE Private Cloud AI
"Small - Expanded" configuration meets their needs. They now need to generate a final, quotable Bill of Materials (BOM).
What is the most direct and efficient method for the sales team to create this BOM?
Answer: C
NEW QUESTION # 45
A customer in the media and entertainment industry wants a solution to accelerate the creation of 3D animations and renderings. Their artists need to be able to generate complex visual AI content quickly.
The company has a mature AI practice and requires a powerful, data center-based solution.
Which HPE ProLiant server and NVIDIA GPU combination is purpose-built for these generative visual AI workloads?
Answer: B
NEW QUESTION # 46
An enterprise wants to deploy pre-trained foundation models from various sources for multiple business units. A key requirement is to simplify and standardize the deployment process, regardless of the model's origin. They want a solution that packages models into scalable, optimized, and easy-to-use microservices with a standard API.
Which component of the NVIDIA AI Enterprise software suite directly addresses this need?
Answer: B
NEW QUESTION # 47
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: C
NEW QUESTION # 48
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