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Network Appliance NetApp Certified AI Expert Sample Questions:

1. A research institute is designing an infrastructure to support its entire AI drug discovery pipeline.
The pipeline has two distinct workload requirements:
1. Training: A team of data scientists needs to train several large transformer models simultaneously using a 500 TB dataset of genomic sequences. This process requires maximum data throughput to keep the GPUs saturated.
2. Inference: Once trained, the models are deployed to an internal web portal where researchers submit individual protein sequences for analysis. These queries must return results with the lowest possible latency.
Which infrastructure design best satisfies both requirements? (Choose 2.)

A) Use a single, large Cloud Volumes ONTAP instance in a public cloud to handle both workloads to simplify management.
B) Configure QoS minimums on the training volumes to ensure they do not impact inference performance.
C) Deploy a large NetApp ASA cluster with GPUDirect Storage enabled for the training environment.
D) Implement NetApp FlexCache on smaller nodes at the network edge to serve the inference requests.
E) Use NetApp StorageGRID as the primary storage for both the training and low-latency inference workloads.

2. A media company is building a new generative AI service. The project has two main components:
1. Data Lake & Fine-Tuning: A 300 TB repository of unstructured data (videos, images, text) stored as objects will be used to fine-tune a foundational model. This process requires a scalable, cost-effective storage solution that can integrate with cloud-native data processing tools like Apache Spark.
2. Inference & RAG: The fine-tuned model will be used in a customer-facing application that leverages Retrieval-Augmented Generation (RAG). To ensure low-latency responses, the RAG component requires extremely fast lookups from a 10 TB vector database.
The company needs a solution that optimizes both cost and performance for this entire lifecycle.
Which combination of NetApp technologies provides the most appropriate solution for this scenario?

A) Use NetApp E-Series for the data lake and a NetApp ASA system for the vector database.
B) Use NetApp Cloud Volumes ONTAP for the data lake and NetApp StorageGRID for the vector database.
C) Use a single, large NetApp ASA system for both the object data lake and the vector database.
D) Use NetApp StorageGRID for the data lake and a NetApp ASA system for the vector database.

3. The Chief Information Security Officer (CISO) is concerned about the risk of a ransomware attack encrypting the critical vector database hosted on the NetApp AFF A-Series. The CISO wants a solution that can proactively detect and block a live attack in real-time, not just recover from a backup after the fact.
Which NetApp security feature should the architect enable on the vector database volume to meet this requirement?

A) NetApp Volume Encryption (NVE)
B) NetApp SnapLock (Compliance Mode)
C) Autonomous Ransomware Protection (ARP)
D) Multi-Admin Verification (MAV)

4. An AI architect is designing a solution for a legal firm. The primary goal is to allow lawyers to ask natural language questions about case law stored in a private, 50 TB document repository.
The key project constraints are as follows:
Project_Goal: Answer questions using proprietary, real-time legal documents.
Constraint_1: Must not alter the foundational LLM's weights due to compliance.
Constraint_2: Case law database is updated daily with new rulings.
Constraint_3: All generated answers must be traceable to a source document.
Which technology should the architect choose as the core of this solution?

A) A Retrieval-Augmented Generation (RAG) architecture.
B) A predictive AI model to classify legal documents.
C) A new LLM trained from scratch on the legal documents.
D) A fine-tuning pipeline to update the LLM daily.

5. The firm's CFO is concerned about the rising costs of the on-premises AI infrastructure. A storage utilization report shows that of the 200 TB of data on the high-performance AFF A-Series, 150 TB consists of inactive, older versions of product documents that are rarely accessed but must be kept online for regulatory reasons.
The current storage landscape is:
- Performance Tier: NetApp AFF A-Series (200 TB used)
- Capacity Tier: NetApp StorageGRID (1.5 PB used)
What is the most effective and automated solution to reduce the storage cost of the performance tier without impacting data accessibility?

A) Purchase an additional, larger AFF A-Series system to gain better storage efficiency through deduplication.
B) Manually identify and delete the 150 TB of inactive data from the AFF A-Series.
C) Implement NetApp FabricPool to automatically tier the inactive data blocks from the AFF A-Series to the StorageGRID system.
D) Use NetApp SnapMirror to replicate the entire 200 TB volume to the StorageGRID system and then delete the source.

Solutions: