Try HP : HPE2-B08 valid & accurate questions and answers

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. Computer Vision / Intelligent Video Analytics
• B. Drug Discovery
• C. Recommender Systems
• D. Natural Language Processing (NLP)

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

A customer is building a large-scale AI training cluster using HPE Private Cloud AI.
They have two main requirements for the storage solution:
1. It must provide extremely high throughput and low latency to feed data to a large cluster of NVIDIA H100 GPUs.
2. It must be able to scale performance and capacity independently to accommodate future growth without costly overprovisioning.
The architect is proposing HPE GreenLake for File Storage.
Which architectural features of this solution directly address the customer's requirements? (Select all that apply.)
```
Customer Requirements:
1. High performance for AI training workloads.
2. Independent scaling of performance and capacity.
```

• A. It uses a disaggregated architecture, allowing controller nodes (performance) and storage shelves (capacity) to be scaled separately.
• B. It includes HPE Data Fabric, providing a global namespace across the worker nodes' local drives.
• C. It is managed exclusively through a command-line interface (CLI) for maximum control.
• D. It supports GPUDirect Storage (GDS) over a high-speed NVMe-oF (RoCE) network, enabling a direct, low-latency path between storage and GPUs.
• E. It relies on traditional hard disk drives (HDDs) for cost-effective capacity, with a small flash tier for caching.

A customer is using the HPE Intelligent Configurator to determine the correct size for an HPE Private Cloud AI solution. Their primary use case is a text generation chatbot for internal HR support.
What is the MOST critical piece of information the customer must provide to the sizing tool to get an accurate recommendation for the number and type of GPUs required?

• A. The number of ML engineers who will maintain the model.
• B. The physical location of the data center where the solution will be deployed.
• C. The estimated number of concurrent users who will be querying the chatbot.
• D. The brand of networking switches used in their existing data center fabric.

A data science team has trained a deep learning model for image classification. While the model achieves 99.8% accuracy on the training dataset, its accuracy drops to only 75% on a new, unseen validation dataset.
The team provides the following training metrics:
```
- Training Epochs: 500
- Training Dataset Size: 1,000 images
- Model Parameters: 15 million
- Training Accuracy: 99.8%
- Validation Accuracy: 75.3%
```
What is the most likely cause of this performance discrepancy?

• A. The model is overfitting to the training data and cannot generalize to new data.
• B. The model has too few parameters to learn the features effectively.
• C. The learning rate used for training was set too low.
• D. The model is underfitting due to an insufficient number of training epochs.