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What Are Data Parallelism and Model Parallelism in AI?
Training large artificial intelligence (AI) models requires a lot of computational power and memory. As models grow bigger, training them becomes more complex and time-consuming. To handle this challenge, researchers and engineers use techniques called data parallelism and model parallelism. These methods help distribute the workload across multiple computers or processing units, making training faster and more efficient.
Written byDustin Collins
Published onAugust 4, 2025
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