An administrator has been asked to install Nutanix Enterprise AI and is defining the NFS storage class for storing models.
What type of access mode needs to be defined?

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An Accounting Department is thrilled with the RAG Application that the Application & Data Science Teams recently rolled out. However, they provided some feedback that sometimes (approximately 20% of the time), the documents retrieved are not relevant to their prompts or are too generiC.
During development, there was extensive testing between models to make sure the best possible model was selecteD. The Accounting Department emphasizes that when the responses use the right documents, the results are very good and they are pleased with the completeness, accuracy, and coherence of those responses.
What would be a way to address the irrelevant RAG results without having to rebuild the entire workflow?

An administrator is deploying the required infrastructure on-premise using NKP on Nutanix to install NAI.
Which type of storage should be created during the deployment process to save the models?

What is the correct endpoint PATH that is displayed in the NAI Dashboard?

An administrator attempts to import a pre-trained model into Nutanix Enterprise AI (NAI), but the model fails to appear in the deployment list, and endpoint creation is unavailable.
Which action should the administrator take to troubleshoot the issue?