The answer
Yes. Some adaptation methods train selected parameters or add small trainable components. Their usefulness depends on the task and the evaluation results.
How does adjusting parameters improve an AI model’s predictions?
Can parameters be updated without retraining the entire model?
More FAQs in How does adjusting parameters improve an AI model’s predictions?
No. Parameters are shared across examples, so an update can improve some predictions while worsening others. Training aims to improve an aggregate objective.
Gradients describe local behavior around current parameter values. Very large steps can move beyond the region where that information predicts a useful direction.
Still have questions?
Browse all our FAQs or reach out to our support team
Want to upskill yourself?
Your learning library
Small steps. Big possibilities.
Find your next course. Build something great.