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Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q69-Q74):

NEW QUESTION # 69
An AI training job is running slower than expected. The infrastructure team suspects a compute bottleneck. The job involves processing high-resolution images with a complex convolutional neural network (CNN). They review the logs from the training script.
Epoch 1/100 - 3600s - loss: 1.253 - acc: 0.54
...
CPU_Utilization_During_Epoch: 99% (all cores)
GPU_0_Utilization_During_Epoch: 8%
GPU_1_Utilization_During_Epoch: 7%
...
Epoch 2/100 - 3610s - loss: 1.102 - acc: 0.61
What is the most likely cause of the poor training performance?

A. The storage system cannot deliver data fast enough to the compute node.
B. The model is too simple and does not effectively utilize the GPU's parallel processing capabilities.
C. The training script is CPU-bound, likely performing data augmentation or preprocessing on the CPU instead of offloading it to the GPUs.
D. The network is saturated, preventing the GPUs from receiving data.

Answer: C

NEW QUESTION # 70
An architect is designing an AI solution for a European hospital chain to analyze patient diagnostic scans. The project is subject to strict GDPR regulations, which mandate that patient data cannot leave the sovereign territory. The application also requires near-instantaneous results for physicians reviewing the scans in the hospital.
Which deployment model best satisfies these security and performance requirements?

A. A hybrid model using a public cloud for training and on-premises for inference.
B. A centralized public cloud deployment in North America for maximum scalability.
C. An on-premises private cloud for training combined with edge deployments in each hospital for inference.
D. A multi-cloud strategy using different providers for training and inference to avoid vendor lock-in.

Answer: C

NEW QUESTION # 71
A data scientist is working on a new model and needs a flexible environment for interactive data exploration, code development, and quick visualizations. A DevOps engineer is responsible for deploying the finalized model into a production pipeline that must run automatically every night without manual intervention.
Which tools are best suited for each of these roles?

A. Both the data scientist and the DevOps engineer should use automated production pipelines.
B. Both the data scientist and the DevOps engineer should use Jupyter Notebooks.
C. The data scientist should use a production pipeline, and the DevOps engineer should use a Jupyter Notebook.
D. The data scientist should use a Jupyter Notebook, and the DevOps engineer should use an automated production pipeline (e.g., Kubeflow Pipelines, Airflow).

Answer: D

NEW QUESTION # 72
Given the firm's requirements for using a private, constantly updated knowledge base and the strict mandate for data traceability, which AI architecture is the most appropriate foundation for the "Advisor Assistant" chatbot?

A. A fine-tuning architecture where a base LLM is continuously retrained on the entire document repository.
B. A Retrieval-Augmented Generation (RAG) architecture that retrieves relevant context from a local vector database to enrich prompts sent to the LLM.
C. A standalone LLM deployed in an air-gapped environment with no access to the document repository.
D. A predictive AI model trained to forecast market trends.

Answer: B

NEW QUESTION # 73
An AI architect needs to design a complete, end-to-end data pipeline for a new generative AI application at a financial services firm. The application will allow internal analysts to query a massive, 500 TB archive of historical market data and reports to generate summaries. The firm has the following environment and requirements:
Data_Sources: A mix of on-premises ONTAP filers and StorageGRID S3 buckets.
Requirement_1: All queries must be answered using only the private data archive.
Requirement_2: All generated summaries must provide citations to the source reports.
Requirement_3: All data containing client PII must be identified and excluded from the LLM context.
Requirement_4: The solution must be cost-effective for the large, mostly-read data archive.
Which set of actions and technologies constitutes the most robust and compliant solution?
(Select all that apply.)

A. During the RAG retrieval step, filter out any documents tagged as containing PII by BlueXP classification before sending them to the LLM.
B. Use NetApp XCP to perform a one-time migration of all data from the ONTAP filers to the StorageGRID data lake.
C. Deploy BlueXP classification to scan the entire StorageGRID data lake to identify and tag all files containing PII.
D. Implement a Retrieval-Augmented Generation (RAG) architecture to meet the requirements for private data usage and source citation.
E. Fine-tune a foundation model on the entire 500 TB dataset to ensure it understands the financial context.
F. Use SnapMirror to replicate the StorageGRID data lake to a high-performance NetApp ASA system for faster query performance.

Answer: A,B,C,D

NEW QUESTION # 74
......

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Valid Test NS0-901 Tips & Valid Dumps NS0-901 Ebook

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Valid Dumps NS0-901 Ebook & NS0-901 Interactive Questions

Network Appliance NetApp Certified AI Expert Exam Sample Questions (Q69-Q74):

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