inefficient because that optimization process requires time to actually learn how to learn from data and lastly these methods do have an intertwined model and architecture essentially the the model that you're using to make predictions about data points is inherently intertwined with the model that you're using to to take in the training data points as input okay as I mentioned before optimization based approaches can very nicely handle varying K and large K the structure also lends well to out of distribution tasks and one of the