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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: HPE ProLiant Gen12 for AI | 20% | - GPU integration and configuration - AI-optimized compute design - Server architecture and components |
| Topic 2: Troubleshooting HPE Private Cloud AI | 10% | - Issue diagnosis and resolution - Performance tuning and optimization |
| Topic 3: HPE AI Essentials: Data Analytics and Data Science | 15% | - Data pipelines and processing - Analytics and machine learning tools |
| Topic 4: Integration with Third-Party Platforms | 15% | - Red Hat OpenShift and Kubernetes integration - VMware integration |
| Topic 5: High Performance Computing (HPC) Design and Management | 10% | - Architecture and scaling - Management and monitoring |
| Topic 6: Solution Optimization and Security | 5% | - Security best practices - Efficiency and resilience |
| Topic 7: NVIDIA AI Enterprise and Model Serving | 10% | - Software deployment and management - Model serving architecture and optimization |
| Topic 8: AI Workshops and HPE AI Essentials Platform | 15% | - Platform capabilities and deployment - Customer engagement and assessment |
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NEW QUESTION # 52
An HPE Private Cloud AI customer has a model deployed with HPE Machine Learning Inference Software (MLIS). You have helped the customer further fine-tune that model. Now the customer would like to test the new model by directing 10% of traffic to it. What should you do?
Answer: B
Explanation:
MLIS supports canary rollout for a new model version by assigning a traffic percentage, such as
10%, to the canary while the existing model continues receiving the remaining traffic.
NEW QUESTION # 53
What is one way that HPE minimizes costs for the HPE Private Cloud AI Developer System?
Answer: B
Explanation:
A is correct. The HPE Private Cloud AI Developer System is positioned as a smaller, cost-conscious configuration for development and proof-of-concept work. Integrating file and object storage into the AI- optimized node reduces the need to purchase, cable, power, and administer a separate external storage tier for the entry configuration. That consolidation lowers infrastructure cost while preserving the data-access patterns required by notebooks, model assets, and AI development workflows.
The remaining choices contradict the design intent of HPE Private Cloud AI. An AI-optimized node is not made cost-effective by eliminating GPU acceleration and using CPU-only compute; doing so would undermine the target AI workload. HPE also does not reduce value by stripping out the integrated software toolchain. The platform's advantage is precisely the curated, validated software environment. NVIDIA AI Enterprise support is likewise a core differentiator of HPE Private Cloud AI with NVIDIA rather than an optional capability removed to save money.
For exam purposes, distinguish architectural consolidation from functional reduction. HPE minimizes entry- system cost by integrating necessary infrastructure components, not by removing the accelerated-compute or enterprise-AI capabilities that define the solution.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 1 "HPE ProLiant Gen12 for AI" and HPE solutions for AI; HPE Private Cloud AI engineered-system and Developer System materials.
NEW QUESTION # 54
What is one role played by the retriever reranking NIM in the NVIDIA NeMo Retriever pipeline?
Answer: A
Explanation:
The reranking NIM re-scores candidate passages retrieved from the vector database and ranks them by relevance to the user query, so the best context is passed to the LLM.
NEW QUESTION # 55
A customer wants to manage the full lifecycle of their HPE ProLiant Gen11 servers - including firmware updates, monitoring, and remote console access - from a single cloud-based console without deploying an on-premises management appliance. Which HPE solution should the integrator recommend?
Answer: C
Explanation:
HPE Compute Ops Management is the cloud-based, GreenLake-delivered management platform for ProLiant/Synergy/Apollo systems, providing lifecycle management, monitoring, and remote console access without requiring a local management appliance. HPE OneView is typically deployed on-premises (or as a VM), Insight Remote Support is focused on support-case automation, and SIM is a legacy product.
NEW QUESTION # 56
A customer needs to deploy a NIM LLM with HPE Machine Learning Inference Software running on HPE Private Cloud AI (AI Essentials 1.6.1).
What is one option for the image for serving the model?
Answer: B
Explanation:
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 5 "Serving NIMs with HPE Machine Learning Inference Software"; HPE AI Essentials/MLIS registry documentation and release-history notes.
NEW QUESTION # 57
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