The taming function in TheoPouLa differs from traditional preconditioners in Adam-type optimizers in several key ways. In Adam-type optimizers, the preconditioner Vn is used to adjust the step size based on the variance of the stochastic gradient. This can lead to issues when the denominator dominates the numerator, causing a vanishing gradient problem. On the other hand, TheoPouLa uses an element-wise taming function that scales the effective learning rate for each parameter individually. This allows for better control over super-linearly growing gradients and prevents them from dominating the optimization process.