HPE Private Cloud AI Solutions - HPE2-B08

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HP HPE2-B08 Exam Syllabus Topics:

HPE Private Cloud AI Solutions Sample Questions:

1. An architect is in a discovery call with a customer who describes their project: "Our primary goal is to take our massive, proprietary dataset of chemical compound interactions and continuously update our foundational AI model's internal parameters to create a new, specialized model for drug discovery. This process runs 24/7 on a large GPU cluster." How should the architect classify this primary AI workload?

A) AI Inferencing
B) Edge Computing
C) Retrieval-Augmented Generation (RAG)
D) AI Model Training / Fine-tuning

2. An architect is designing an AI solution for a financial services company that needs to build a chatbot.
The chatbot must answer customer queries using the company's latest internal policy documents, which are updated daily. The company has a limited budget and no data scientists available for a lengthy model retraining project.
Which approach should the architect recommend?

A) Use a pre-trained computer vision model to extract text from the policy documents.
B) Train a new LLM from scratch using only the company's policy documents to ensure data privacy.
C) Fine-tune a pre-trained model daily by retraining it on the entire set of policy documents.
D) Use a pre-trained model and implement a Retrieval-Augmented Generation (RAG) framework.

3. An architect is using the HPE One Config Advanced (OCA) Smart Template for "HPE Private Cloud AI
- Small - Standard".
What is the worker node configuration they should expect to see in the generated Bill of Materials (BOM)?

A) 3x HPE ProLiant DL325 Gen11 servers for management
B) 1x HPE ProLiant DL380a Gen11 server with 4x NVIDIA L40S GPUs
C) 4x HPE ProLiant DL380a Gen11 servers with a total of 16x NVIDIA H100 NVL GPUs
D) 2x HPE ProLiant DL380a Gen11 servers with a total of 8x NVIDIA L40S GPUs

4. A customer who is an "AI Beginner" wants to start an AI inferencing project at their edge locations.
Their goal is to analyze security camera feeds to help prevent theft. They have a limited budget and IT staff at the edge sites.
Which HPE AI solution is the most appropriate to position for this specific scenario?

A) HPE Private Cloud AI with NVIDIA
B) NVIDIA DGX Systems
C) HPE Cray systems
D) AI-optimized HPE ProLiant DL servers
E) An HPE AI Services - Transformation Workshop

5. In a Natural Language Processing (NLP) task, what is the role of a tokenizer?

A) To train the neural network using backpropagation.
B) To encrypt the input text to ensure data privacy during model training.
C) To convert a sentence of raw text into a sequence of numerical tokens that a model can process.
D) To apply a final activation function to determine the output class.

Solutions: