HPE Private Cloud AI Solutions : HPE2-B08 Exam

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HP HPE2-B08 Exam Syllabus Topics:

HPE Private Cloud AI Solutions Sample Questions:

1. 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) A fully connected, feedforward neural network
C) Convolutional Neural Network (CNN)
D) Transformer model

2. An architect is designing an AI solution to create a medical chatbot that assists doctors by answering questions based on the latest published medical research. The system must be highly reliable, and its answers must be traceable to the source publications. The customer has highlighted that their internal data science team lacks the expertise for complex model retraining but can manage data ingestion pipelines.
Given the customer requirements, which architectural components should the architect include in the solution design? (Select all that apply.)
```
Customer Requirements:
- AI Use Case: Medical Research Q&A Chatbot
- Key Constraint: Information must be current and verifiable.
- Team Skills: Limited AI model training expertise.
- Data Source: Continuously updated database of medical journals.
```

A) A process for daily fine-tuning of the base LLM on all new research papers.
B) A Retrieval-Augmented Generation (RAG) framework to query the vector database.
C) A data ingestion and embedding pipeline to process and add new research to the vector database.
D) An edge-optimized server for model deployment in individual hospital rooms.
E) A vector database to store embeddings of the medical research papers.
F) A pre-trained, general-purpose Large Language Model (LLM).

3. When a developer deploys an AI model using an NVIDIA Inference Microservice (NIM) on HPE Private Cloud AI, the NIM automatically detects the underlying NVIDIA GPU hardware.
The developer sees the following status message upon deployment:
```
NIM Status:
- Model: mistral-7b-instruct-v0.2
- Status: Running
- Engine Profile: Selected 'TensorRT-LLM FP8' for optimal latency on detected Hopper-class GPU.
```
What does the selection of the 'TensorRT-LLM FP8' engine profile indicate?

A) The underlying GPU supports the Hopper architecture, and NIM has optimized the model using a lower precision format for faster performance.
B) The model is being automatically fine-tuned by the NIM using the TensorRT framework.
C) The NIM container has failed because it requires an FP32 profile to run.
D) The NIM container is running on a CPU-only node and is emulating a GPU.

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

5. A customer is considering the HPE Private Cloud AI solution. They need to run a moderately sized RAG application for 150 users. They do not have any fine-tuning requirements.
Why would an architect recommend a "Medium" configuration over a "Large" configuration for this customer?

A) The Medium configuration has more storage capacity than the Large configuration.
B) The Medium configuration is the only one that includes the HPE AI Essentials software.
C) The L40S GPUs in the Medium configuration are more cost-effective and power-efficient for this specific inference-heavy workload.
D) The Large configuration does not support Retrieval-Augmented Generation (RAG).

Solutions: