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What are Weights?

Weights are the numerical parameters within a neural network that determine the strength of connections between artificial neurons and ultimately shape how the model processes information. During training, these weights are continuously adjusted through algorithms like backpropagation to minimize errors and improve the model's predictions. The learned weights represent the model's "knowledge"—a trained AI model is essentially a specific configuration of billions of these weight values that encode patterns discovered from training data.

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Weights mentioned at Stanford HAI

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