In machine learning, a scaling law predicts how model performance improves with more data, parameters, or compute. It guides resource allocation for training large AI systems. Researchers and engineers use it to optimize costs and accuracy. Companies benefit by building more efficient models, while developers gain insights for deploying smarter, faster applications.
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