HP HPE2-B08 問題練習

Question No : 1
What are important considerations when evaluating AI model performance? (Select two.)

• A.Preventing AI models from making autonomous decisions
• B.Computational efficiency and resource utilization
• C.Ensuring all training data is manually labeled
• D.Model accuracy and precision

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Question No : 2
What are key networking considerations for AI workloads in HPE Private Cloud AI? (Select two.)

• A.Low-latency networking for high-speed AI data transfers
• B.Limiting AI workloads to basic Ethernet connections
• C.High-bandwidth interconnects like InfiniBand for large AI models
• D.Using standard LAN infrastructure without optimization

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Question No : 3
What infrastructure components in HPE Private Cloud AI enable scalability for AI workloads? (Select two.)

• A.Restricting compute expansion in multi-GPU setups
• B.High-speed interconnects for distributed AI training
• C.Limiting AI workloads to single-node systems
• D.Modular server architecture for workload expansion

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Question No : 4
How does HPE support AI deployment at the edge?

• A.Through HPE Edgeline servers integrated with NVIDIA AI software
• B.By limiting AI workloads to cloud-based systems
• C.By restricting edge AI to CPU-only configurations
• D.By requiring AI models to be processed in traditional data centers

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Question No : 5
A company wants to build an AI-powered chatbot for customer support.
Which AI approach should they use?

• A.Rule-based programming
• B.Natural Language Processing (NLP)
• C.Manual customer service responses
• D.Static web scripts

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Question No : 6
What are key benefits of using HPE GreenLake for AI workloads? (Select two.)

• A.AI-as-a-Service with scalable deployment options
• B.Cloud-based AI training with flexible resource management
• C.Limiting AI workloads to fixed configurations
• D.Preventing automation in AI model execution

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Question No : 7
How does One Config Advanced (OCA) help in building an HPE Private Cloud AI configuration?

• A.By automating AI training pipelines
• B.By replacing manual AI workload tuning
• C.By selecting optimal hardware and software components
• D.By enforcing static AI configurations

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Question No : 8
What are characteristics of supervised and unsupervised learning? (Select two.)

• A.Supervised learning uses labeled data for training
• B.Unsupervised learning identifies patterns in unlabeled data
• C.Supervised learning is used for clustering similar data points
• D.Unsupervised learning requires predefined outputs

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Question No : 9
In which industries is AI commonly used? (Select two.)

• A.Healthcare for predictive diagnostics
• B.Retail for supply chain management
• C.Manual data entry automation
• D.Traditional file storage management

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Question No : 10
A manufacturing company wants to use AI to predict machinery failures before they occur.
Which AI approach should they use?

• A.Anomaly detection using machine learning models
• B.Traditional statistical reporting
• C.Manual review of all machine logs
• D.Batch processing of historical data without real-time updates

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Question No : 11
How does Machine Learning (ML) differ from traditional AI?

• A.ML allows systems to learn from data without explicit programming
• B.ML is rule-based, whereas AI is purely statistical
• C.AI only works with structured data, while ML processes unstructured data
• D.AI is limited to cloud environments, while ML requires on-premises hardware

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Question No : 12
What are key storage considerations for AI workloads? (Select two.)

• A.Using only traditional HDDs for AI model execution
• B.Avoiding AI-specific optimizations in storage architecture
• C.High-bandwidth storage for real-time AI data processing
• D.Scalable storage solutions for large AI model datasets

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Question No : 13
A retail company wants to deploy an AI-powered recommendation engine that can scale dynamically with customer data growth.
What is the best approach?

• A.Private cloud AI with scalable storage and compute resources
• B.On-premises fixed-size AI deployment
• C.Manual dataset review without AI integration
• D.Restricting AI inferencing to predefined datasets

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Question No : 14
A global research institution is selecting an AI configuration for deep learning workloads.
What key components should they prioritize? (Select two.)

• A.HPE Apollo 6500 servers with NVIDIA GPUs
• B.High-speed InfiniBand networking for distributed AI training
• C.Standard LAN with limited bandwidth
• D.Low-power CPUs with HDD storage

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Question No : 15
A retail business wants to implement AI for customer insights and sales forecasting.
What AI techniques should they consider? (Select two.)

• A.Predictive analytics for demand forecasting
• B.Natural language processing (NLP) for customer sentiment analysis
• C.Using manual customer surveys exclusively
• D.Restricting AI use to in-store data only

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