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Are you considering taking the Nutanix NCP-AI exam? Passing this exam can be a challenge if you don't prepare with the right study material. Fast2test provides accurate and authentic Nutanix NCP-AI Exam Questions to help you prepare for the Nutanix Certified Professional - Artificial Intelligence v6.10. Fast2test strives to provide quality information and a comfortable learning environment for Nutanix NCP-AI Exam candidates. The study material is available in two formats: Nutanix NCP-AI exam questions in pdf format and an online Nutanix NCP-AI practice test engine. Both formats are designed to help you clear the Nutanix Certified Professional - Artificial Intelligence v6.10 (NCP-AI) with ease.
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Nutanix Certified Professional - Artificial Intelligence v6.10 Sample Questions (Q27-Q32):
NEW QUESTION # 27
An administrator observes that inference requests to Nutanix Enterprise AI are experiencing increased latency. After accessing the Infrastructure Usage and Health page, the administrator finds that the Service Health status is marked as Critical, and the GPU utilization on one node is consistently at 100%, while other nodes show moderate usage.
What is the most appropriate next step to resolve the performance issue?
- A. Disable inference endpoints on the overloaded node.
- B. Increase the memory allocation for the node with high GPU usage.
- C. Restart the Kubernetes cluster to reset all node metrics and clear the Critical status.
- D. Rebuild the endpoint to include multiple instances.
Answer: D
NEW QUESTION # 28
What does the Sample Request code include?
- A. Endpoint URL and API key
- B. User credentials and API key
- C. GPU type and max_tokens
- D. Endpoint URL and GPU type
Answer: B
NEW QUESTION # 29
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. 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.
- D. Consult the Hugging Face documentation for the specific LLM to review its training data, intended use cases, and capabilities.
Answer: D
NEW QUESTION # 30
Which GPU is currently supported for Nutanix AI deployment?
- A. V100
- B. T4
- C. L4
- D. A100
Answer: D
NEW QUESTION # 31
An administrator is responsible for monitoring access to the Nutanix Enterprise AI (NAI) platform and must ensure that any unusual activity, such as excessive access requests from specific users or IP addresses, is detected in real time. The administrator has discovered that the NAI Dashboard lacks the detail required to detect this type of activity.
What is the most effective method for the administrator to detect such outlier behavior and ensure a timely response?
- A. Rely on scheduled reports to detect anomalies in user access behaviour after they have occurreD.
- B. Enable basic logging for access events without configuring real-time alerts for anomalies.
- C. Continuously monitor the system manually and log out users suspected of unusual activity without further analysis.
- D. Implement Grafana to analyze user access patterns and flag any anomalies for further investigation.
Answer: D
NEW QUESTION # 32
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