> I am sure a lot of work (and time) went into this but what's the point? If the model is not as good and the original then the applications are limited and the

> I am sure a lot of work (and time) went into this but what's the point? If the model is not as good and the original then the applications are limited and the training time is moot. If the several orders of magnitude (two in this case) improvement can be used to train other models, that's quite a thing no?