brainstorming on this: it might be a way that a model can "learn" while being deployed.

if a model could do a self optimization pass over its weights every night, and change the weights ever so slightly to have a better fitting performance, this would be quite a game changer.

the difficulty is selecting the direction in which to shift the weights, and the sheer size of frontier models.