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.)

• A. A Convolutional Neural Network (CNN)
• B. A model architecture that includes pooling layers to reduce spatial dimensions
• C. A basic, fully connected Artificial Neural Network (ANN)
• D. A model architecture that includes convolutional layers for feature extraction
• E. A transformer-based model designed for Natural Language Processing (NLP)

A customer states they need an AI solution for a "summarization" use case that will be accessed by approximately 75 concurrent users. The underlying data is updated frequently, so RAG will be required.
When using the HPE Intelligent Configurator, which three inputs are mandatory to get an initial sizing recommendation?

• A. Number of users, Preferred GPU model, Data center location
• B. RAG requirement, Power and cooling capacity, Desired software license term
• C. Use case, Model choice, Network switch preference
• D. Use case, Number of users, RAG requirement

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

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.)

• A. The solution requires a Large configuration.
• B. The key component is the NVIDIA L40S GPU, which is optimized for RAG workloads.
• C. The key component is the HPE ProLiant DL325 server in the management plane.
• D. The solution requires a Medium configuration.
• E. The key component is the NVIDIA H100 NVL GPU, designed for large-scale training and fine-tuning.

An architect is comparing two different models for a text summarization task.
Model A: A Convolutional Neural Network (CNN)
*Model B: A Transformer-based model
Why is the Transformer-based model (Model B) fundamentally better suited for this task?

• A. Transformers can be trained without GPUs, unlike CNNs.
• B. CNNs can only process images, not text.
• C. CNNs require significantly more training data than Transformers.
• D. Transformers use an attention mechanism to understand the contextual relationships between all words in the text, which is critical for summarization.