HPE2-B08 HPE Private Cloud AI Solutions PDF Questions

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2. 1.What key component impacts AI system configuration size? A. Number of GPUs and compute nodes B. Type of networking cables used C. Number of office locations using AI models D. Default storage settings Answer: A 2.What is the primary role of HPE Machine Learning Development Environment (MLDE) in AI workloads? A. To provide an optimized platform for AI model training and lifecycle management B. To replace all cloud-based AI solutions C. To manually configure AI models without automation D. To restrict AI workloads to a single GPU Answer: A 3.How does HPE Ezmeral AI support AI workloads? A. By enabling containerized AI workloads and machine learning pipelines B. By providing network storage for traditional databases C. By enforcing a strict single-tenant model D. By requiring manual deployment of all AI models Answer: A 4.What factors influence an AI deployment strategy? (Select two.) A. AI inference time and response speed B. Manual dataset validation for all AI models C. Security and compliance regulations D. Eliminating automation from AI decision-making Answer: AC 5.What is a critical factor when selecting compute resources for AI workloads in HPE Private Cloud AI? A. The number of high-performance GPUs for parallel processing B. The availability of low-cost CPU-only nodes C. The reliance on traditional database infrastructure D. The requirement for single-threaded processing Answer: A 6.What factors impact AI model performance in different configuration sizes? (Select two.) A. Number of GPUs available for training B. Data pipeline optimization for faster processing C. Restricting AI model retraining D. Preventing AI system upgrades Answer: AB 7.What are the three primary types of AI? A. Narrow AI, General AI, and Super AI 2 / 3

3. B. Rule-Based AI, Neural AI, and Statistical AI C. Cloud AI, Edge AI, and Hybrid AI D. Predictive AI, Descriptive AI, and Prescriptive AI Answer: A 8.An AI research lab requires a high-speed interconnect to handle AI model training data. What should they implement? A. Wireless networking for faster transfers B. Standard Gigabit Ethernet C. HPE Slingshot high-performance interconnect D. Direct-attached storage without network optimization Answer: C 9.What are key differences between AI training and inference? (Select two.) A. Training requires large datasets, while inference uses pre-trained models B. Inference always produces the same output regardless of input data C. Training is typically done on CPUs, while inference is GPU-based D. Inference is real-time and optimized for low-latency predictions Answer: AD 10.What are key benefits of HPE AI software solutions? (Select two.) A. AI model lifecycle management and automation B. Scalable AI deployment across hybrid environments C. Restricting AI model training to on-premises clusters D. Eliminating the need for GPUs in AI processing Answer: AB 11.How does NVIDIAAI Enterprise enhance AI applications in HPE Private Cloud AI? A. By optimizing AI workloads for enterprise environments B. By replacing the need for deep learning models C. By eliminating the requirement for AI hardware acceleration D. By restricting AI workloads to single-cloud environments Answer: A 12.What are key considerations when deploying AI models in HPE Private Cloud AI? (Select two.) A. Avoiding automation in AI workflows B. Storage scalability for AI datasets C. Using CPUs exclusively for AI training D. Model optimization for GPUs Answer: BD 3 / 3