in one of the chats i learned that in machine learning “grok” is the phenomenon whereby, if a model is overtrained for a very long time after the loss bottoms out, it can further generalize far beyond the given dataset, reversing the effects of overfitting. doesn’t sound like it is meant in that sense here.