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What is Scaling?

A plain-English explanation of Scaling (Scaling Laws) — what it means, why it matters, and how it is used in AI.

Scaling
Scaling Laws
Scaling refers to the empirical observation that AI model performance improves predictably as model size, dataset size, and compute budget are increased.
"Scaling laws predicted that making GPT models larger and training them on more data would reliably improve performance."

Also known as: Scaling laws, neural scaling laws, compute scaling

ComputeParametersEmergentTraining

Why does Scaling matter?

Scaling laws guide decisions about how much compute to invest in training.

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