Containers (e.g., Docker) encapsulate AI applications with their dependencies, ensuring consistent execution across diverse environments—from development laptops to production clusters—without manual reconfiguration. They don’t inherently improve model accuracy, generate datasets, or boost GPU speed, focusing instead on portability and reproducibility.(Note: The document incorrectly lists A; B is correct per NVIDIA standards.)
(Reference: NVIDIA AI Infrastructure and Operations Study Guide, Section on Containers in AI Development)
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