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[General] NCP-AI Valid Exam Pdf - NCP-AI Popular Exams

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【General】 NCP-AI Valid Exam Pdf - NCP-AI Popular Exams

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Nutanix NCP-AI Exam Syllabus Topics:
TopicDetails
Topic 1
  • Perform Day 2 Operations: This domain addresses ongoing management including preparing application integration requirements, interpreting and optimizing performance metrics, monitoring access for anomalies, and selecting appropriate LLMs for optimal output.
Topic 2
  • Troubleshoot a Nutanix Enterprise AI Environment: This domain covers diagnosing and resolving performance issues, resource utilization problems, cluster health check failures, and model import or endpoint creation errors.
Topic 3
  • Configure a Nutanix Enterprise AI Environment: This domain focuses on operational setup including onboarding users, importing large language models, creating and securing API endpoints with keys, and delivering these endpoints to consumers.
Topic 4
  • Connect Applications to a Nutanix Enterprise AI Environment: This domain focuses on configuring and validating application connections to endpoints and monitoring endpoint metrics to track application usage and integration performance.
Topic 5
  • Deploy a Nutanix Enterprise AI Environment: This domain covers initial deployment tasks including validating prerequisites, installing Enterprise AI components, and configuring DNS, URLs, and certificates for secure platform operation.

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Nutanix Certified Professional - Artificial Intelligence v6.10 Sample Questions (Q20-Q25):NEW QUESTION # 20
What minimum persistent storage is required for the nai-db app when deploying Nutanix Enterprise AI platform?
  • A. 2 GiB
  • B. 2 TiB
  • C. 4 GiB
  • D. 4 TiB
Answer: C

NEW QUESTION # 21
Which user type is the first AI/ML admin user who installs Nutanix Enterprise AI on the Kubernetes cluster?
  • A. Super User
  • B. AI/ML Admin
  • C. AI/ML User
  • D. Super Admin
Answer: D

NEW QUESTION # 22
Which widget within the Endpoint Details page can an administrator verify the memory usage associated with the endpoint?
  • A. Endpoints (Top 5)
  • B. Number of Compute Instances
  • C. API Requests Trends
  • D. Infrastructure Summary
Answer: D

NEW QUESTION # 23
An administrator is troubleshooting a slow response from an inference endpoint used by multiple separate applications. The administrator has observed a huge increase in requests.
In order to identify which application is generating the huge increase in requests, what could the administrator do?
  • A. Reduce the assigned compute resources.
  • B. Deactivate the inference endpoint.
  • C. Deactivate API keys one at a time.
  • D. Increase the assigned compute resources.
Answer: C

NEW QUESTION # 24
A development team is building a new AI-powered customer service chatbot. They have successfully integrated an LLM from Hugging Face into their application via a Nutanix Enterprise AI (NAI) endpoint. The NAI administrator has confirmed the endpoint is in the 'Active' state, and internal sample requests run from the NAI Endpoint section return an 'accurate' response and 'Succeeded' status.
However, the developers report that the chatbot frequently provides vague or irrelevant answers to user queries, leading to low customer satisfaction scores. They describe the LLM's performance for this specific chatbot task as "suboptimal." What should the administrator advise the developers to do next to improve the quality of the LLM's responses for the customer service chatbot task?
  • A. Increase the number of instances for the NAI endpoint to enhance performance and reduce latency.
  • B. Reseed the initial dataset and reimport the existing LLM within Nutanix Enterprise AI without implementing a RAG platform.
  • C. Consult the Hugging Face documentation for the specific LLM to review its training data, intended use cases, and capabilities.
  • D. Instruct the administrator to check the Kubernetes pod logs for the endpoint to identify any CRASHLOOPBACKOFF or OOMKilled errors that might be affecting model inference.
Answer: C

NEW QUESTION # 25
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