Prominent Features of HP HPE2-B08 Practice Test Questions
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HPE Private Cloud AI Solutions Sample Questions (Q16-Q21):
NEW QUESTION # 16
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. Apply stricter content moderation and safety guardrails to the model's output.
- 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. Retrain the model from scratch using a much larger and more diverse public dataset.
- E. Implement a Retrieval-Augmented Generation (RAG) framework to provide the model with verifiable, external context at inference time.
Answer: C,E
NEW QUESTION # 17
A financial services firm is building a fraud detection application on HPE Private Cloud AI. The application needs to process a continuous stream of transaction data from multiple sources in real time.
The data science team requires a robust platform to build, manage, and execute the complex data pipelines needed to feed the AI model.
Which pre-integrated open-source tool within HPE AI Essentials is the industry standard for orchestrating and managing these complex data workflows and pipelines?
- A. JupyterLab
- B. Prometheus
- C. Apache Airflow
- D. Kyverno
Answer: C
NEW QUESTION # 18
A customer needs to run a generative AI workload at multiple, dispersed edge locations. Each location has significant space and power constraints. The workload is inference-only and does not require the absolute highest performance, but rather a balance of good performance and energy efficiency.
Which HPE ProLiant server and NVIDIA GPU combination is specifically positioned for this type of edge AI use case?
- A. HPE ProLiant DL380a server with NVIDIA H100 NVL GPUs
- B. HPE Cray system with NVIDIA Grace Hopper Superchips
- C. HPE ProLiant DL384 Gen12 server with NVIDIA H200 NVL GPUs
- D. HPE ProLiant DL320 Gen11 server with NVIDIA L4 GPUs
Answer: D
NEW QUESTION # 19
You are positioning HPE Private Cloud AI to a customer who is an "AI Pro" and wants to scale their generative AI efforts.
Which key capabilities of the solution would you emphasize to this customer? (Select all that apply.)
- A. The inclusion of a full-stack, enterprise-supported software suite including NVIDIA AI Enterprise and HPE AI Essentials.
- B. Its turnkey nature, which simplifies deployment and allows their expert team to focus on building models rather than integrating infrastructure.
- C. The option to choose a Large configuration with powerful NVIDIA H100 GPUs and a high-speed RoCE fabric for demanding fine-tuning workloads.
- D. Its ability to run on a single, low-power server for maximum efficiency.
- E. A simple, web-based interface for beginners to learn about AI concepts.
Answer: A,B,C
NEW QUESTION # 20
An architect has used the HPE Intelligent Configurator and determined that a "Medium - Standard" configuration is required.
When creating the final quote in One Config Advanced (OCA), what is the mandatory prerequisite that the customer is responsible for providing for the solution to be valid?
- A. A rack elevation diagram for the data center.
- B. A list of all end-users who will access the system.
- C. A valid, bring-your-own-license (BYOL) for VMware vSphere Foundation (VVF) or VMware Cloud Foundation (VCF).
- D. A subscription to the NVIDIA NGC catalog for downloading AI models.
Answer: C
NEW QUESTION # 21
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