A government agency analyzes satellite imagery to monitor deforestation. The images are extremely large, and the current analytics software cannot process them in a reasonable time. They have access to a supercomputer. What is the best way to use the supercomputer for this analytics workload?

Store the images on the supercomputer's storage but continue processing on the current software

Use a machine learning model to classify the images without processing all the pixels

Use parallel image processing algorithms on the supercomputer to analyze the images concurrently

Reduce the resolution of the images to make them smaller and process them on the current software

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Describe Convergence of AI, High-Performance Computing, and Analytics CERTIFIED-AI-EXPERT Practice Questions (Page 7)

Part of the AI Overview domain, which accounts for 15% of the CERTIFIED-AI-EXPERT exam. NetApp does not publish an official question count, but from its 90-minute exam (~35–60 total, ~5–9 in this domain), expect 1–2 from this objective — we provide 31 practice questions to prepare you well beyond it. (estimate)

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Questions 31–31

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A government agency analyzes satellite imagery to monitor deforestation. The images are extremely large, and the current analytics software cannot process them in a reasonable time. They have access to a supercomputer. What is the best way to use the supercomputer for this analytics workload?
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Describe Convergence of AI, High-Performance Computing, and Analytics CERTIFIED-AI-EXPERT Practice Questions (Page 7)

Questions 31–31

A government agency analyzes satellite imagery to monitor deforestation. The images are extremely large, and the current analytics software cannot process them in a reasonable time. They have access to a supercomputer. What is the best way to use the supercomputer for this analytics workload?

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