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HPE Private Cloud AI Solutions Sample Questions:
1. A large financial institution, a known "Deployer of AI at scale," needs to train a next-generation fraud detection model. This new model has over a trillion parameters, significantly larger than their current models, and requires an exascale-class computing solution to be trained in a reasonable timeframe.
Which HPE AI solution should be positioned to meet this customer's demanding requirement?
A) HPE Private Cloud AI with NVIDIA, Large configuration
B) AI-optimized HPE ProLiant DL servers
C) HPE Cray systems
D) HPE GreenLake for File Storage
2. You are in a meeting with the VP of Manufacturing for a large industrial company. She describes their AI program as follows:
"We have a formal Center of Excellence for AI that reports directly to the CTO. Our strategy is to scale our successful predictive maintenance models across all 25 of our global plants. We have standardized on a consistent cloud and data governance strategy for all AI projects and have clear ROI targets for reducing downtime." Based on this description, which AI maturity level best describes this customer?
A) AI Curious
B) AI Pro
C) Early AI user
D) AI Beginner
3. A development team reports that their custom-trained Large Language Model (LLM) is "hallucinating"
- generating factually incorrect or nonsensical information, especially when asked questions outside the scope of its training data. The model was created by fine-tuning a foundation model on a large but static internal dataset. The team wants to improve the model's factual accuracy and reliability without embarking on a new, large-scale training project.
Which are the most appropriate strategies to mitigate this issue? (Choose 2.)
A) Retrain the model from scratch using a much larger and more diverse public dataset.
B) Reduce the "temperature" setting during inference to make the model's output less random and more focused.
C) Increase the number of hidden layers in the model's architecture.
D) Implement a Retrieval-Augmented Generation (RAG) framework to provide the model with verifiable, external context at inference time.
E) Apply stricter content moderation and safety guardrails to the model's output.
4. A customer in the public sector wants to use AI to analyze live video feeds from city-wide cameras to automate public safety tasks like detecting traffic accidents or identifying security threats in real-time.
This is their first major AI initiative.
Which AI use case does this scenario represent?
A) Drug Discovery
B) Computer Vision / Intelligent Video Analytics
C) Natural Language Processing (NLP)
D) Recommender Systems
5. An AI development team is training a large language model that exceeds the memory capacity of a single GPU. To continue training, they need to distribute the workload across multiple GPUs within the same server.
Which combination of HPE server and NVIDIA technology is specifically designed to provide a high- bandwidth, direct communication path between GPUs, bypassing the PCIe bus for improved performance in multi-GPU training?
A) HPE ProLiant DL380a Gen11 server with GPUDirect Storage (GDS)
B) HPE ProLiant DL325 Gen11 server with NVIDIA L4 GPUs
C) HPE ProLiant DL380a Gen12 server with an NVIDIA NVLink Bridge
D) HPE Alletra Storage MP with RoCE-capable network adapters
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: B | Question # 3 Answer: B,D | Question # 4 Answer: B | Question # 5 Answer: C |

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