The answer
No. Parameters are shared across examples, so an update can improve some predictions while worsening others. Training aims to improve an aggregate objective.
How does adjusting parameters improve an AI model’s predictions?
Does every parameter update improve every prediction?
More FAQs in How does adjusting parameters improve an AI model’s predictions?
Gradients describe local behavior around current parameter values. Very large steps can move beyond the region where that information predicts a useful direction.
Yes. Some adaptation methods train selected parameters or add small trainable components. Their usefulness depends on the task and the evaluation results.
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