Weak-to-Strong Generalization

Weak-to-strong generalization is a machine learning technique in which a weak model is used to train a strong model. This can be a useful way to improve the performance of a model, as it allows the model to learn from a larger dataset than it would be able to on its own.

Weak-to-strong generalization is a key component of any successful AI strategy, as it can help to improve the performance of your models.