Online Access Free HPE2-B08 Exam Questions

A company has developed a custom fraud detection model. Their data science team wants to deploy this model into production for other applications to use. They want to avoid the complexity of manually configuring the serving environment, optimizing for hardware, and creating a scalable API endpoint.
How does using an NVIDIA Inference Microservice (NIM) within HPE Private Cloud AI simplify this process?

• A.NIM provisions the underlying Kubernetes cluster and physical servers.
• B.NIM automatically fine-tunes the model on new data to improve its accuracy.
• C.NIM provides a framework that packages the model into an optimized, ready-to-deploy container with a standard API.
• D.NIM directly connects to the raw data sources to perform data preparation and cleaning.

A customer explains that their data engineers are spending too much time managing disparate data pipelines with a complex set of open-source tools. They are an 'Early AI User' trying to standardize their approach.
Which value proposition of HPE Private Cloud AI directly addresses this specific stakeholder's pain point?

• A.It includes HPE AI Essentials, which provides a unified platform with pre-integrated data pipeline and workflow tools like Apache Airflow and Spark.
• B.It can be deployed in a colocation facility through HPE GreenLake.
• C.It offers a choice of NVIDIA GPUs to accelerate model training.
• D.Its management plane uses three redundant HPE ProLiant DL325 servers for high availability.

An organization is using HPE Private Cloud AI to manage a large, multi-tenant Kubernetes environment for its data science teams. They need to ensure that data access is securely managed and that each team's data is isolated within a logical, policy-driven boundary. Additionally, they need to store and access data from multiple sources, including NFS clients and S3-compatible object stores.
Which software components of the HPE Private Cloud AI stack work together to provide this unified, policy-driven, multi-protocol data access? (Select all that apply.)

• A.HPE Data Fabric
• B.NVIDIA NIM (NVIDIA Inference Microservices)
• C.HPE GreenLake for File Storage
• D.HPE AI Essentials
• E.Kyverno

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

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

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