NCA-AIIO exam dumps

NCA-AIIO practice question 39 of 119

NVIDIA-Certified Associate - AI Infrastructure and Operations. Free level, NVIDIA. Free question with the correct answer and a full explanation.

NCA-AIIO Question 39

Select 2

A company is building an AI-powered recommendation system to serve millions of users globally. The system requires high-performance compute for training large-scale deep learning models and efficient inference deployment. Which NVIDIA solutions would be most suitable for this use case?

  1. A

    NVIDIA DGX Systems

  2. B

    NVIDIA Triton Inference Server

  3. C

    NVIDIA Omniverse

  4. D

    NVIDIA BlueField DPUs

  5. E

    NVIDIA Clara

Show answer and explanation

Correct answers: A, B

Explanation

Building an AI-powered recommendation system requires a combination of high-performance AI training hardware and efficient inference deployment tools. NVIDIA DGX Systems provide the compute power needed for training deep learning models, while NVIDIA Triton Inference Server enables scalable and efficient inference deployment. Other solutions like NVIDIA Omniverse, BlueField DPUs, and Clara are specialized for different use cases and are not applicable in this scenario.

  • A. Correct.

    NVIDIA DGX Systems are designed for high-performance AI training, making them ideal for training large-scale deep learning models required for recommendation systems.

  • B. Correct.

    NVIDIA Triton Inference Server is optimized for efficient deployment of AI inference, making it suitable for serving recommendations to millions of users.

  • C. Incorrect.

    NVIDIA Omniverse is a platform for 3D design collaboration and simulation, which is not relevant to the requirements of a recommendation system.

  • D. Incorrect.

    NVIDIA BlueField DPUs are designed for data center offloading and security, which are not directly relevant to AI model training or inference in this scenario.

  • E. Incorrect.

    NVIDIA Clara is a healthcare-specific platform for medical imaging and genomics, which is not applicable to a recommendation system use case.

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