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HPE Private Cloud AI Solutions Sample Questions:

1. 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) Increase the number of hidden layers in the model's architecture.
C) Reduce the "temperature" setting during inference to make the model's output less random and more focused.
D) Apply stricter content moderation and safety guardrails to the model's output.
E) Implement a Retrieval-Augmented Generation (RAG) framework to provide the model with verifiable, external context at inference time.

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

3. A customer's ML Engineer states, "We need to deploy our trained models, and our top priority is simplifying the process. We want to treat our models like cattle, not pets-packaging them into standardized, optimized containers that we can deploy and scale easily via an API." This statement describes the primary benefit of which software component in the HPE Private Cloud AI stack?

A) NVIDIA NIM (NVIDIA Inference Microservices)
B) Apache Airflow
C) JupyterLab
D) HPE Data Fabric

4. An architect is building a final configuration for an HPE Private Cloud AI solution using One Config Advanced (OCA). After selecting the "HPE Private Cloud AI - Medium Expanded" Smart Template, they review the generated Bill of Materials (BOM).
Which components are characteristic of the Medium Expanded configuration that the architect should expect to see in the OCA-generated BOM? (Select all that apply.)

A) 4x HPE ProLiant DL380a Gen11 Servers
B) 2x HPE Aruba Networking CX 6300M Switches
C) 1x HPE ProLiant DL380a Gen11 Server
D) 2x NVIDIA SN4700M Switches
E) 16x NVIDIA L40S GPUs
F) 16x NVIDIA H100 NVL GPUs

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 DL325 Gen11 server with NVIDIA L4 GPUs
B) HPE ProLiant DL380a Gen11 server with GPUDirect Storage (GDS)
C) HPE ProLiant DL380a Gen12 server with an NVIDIA NVLink Bridge
D) HPE Alletra Storage MP with RoCE-capable network adapters

Solutions: