What are the challenges of using pretrained models in AI?

What are the challenges of using pretrained models in AI?

Some challenges include domain adaptation, bias in training data, and limited interpretability.

Can you explain domain adaptation?

Domain adaptation refers to the difficulty of applying a model trained on one dataset to a different but related dataset.

How can bias in training data affect the model's performance?

Bias can lead to unfair or inaccurate predictions, as the model may learn and reinforce existing stereotypes.

What are some strategies to mitigate these challenges?

Strategies include fine-tuning the model, using diverse training data, and implementing fairness-aware algorithms.