one of the proof points that you know some supervisory training is really figuring out the same relation is the same kind of connecting the concepts connecting them and helping with robustness and generalization and there's some new work from Tim Hendricks this week that I've which I have put in these slides showing that Berkeley as follows are much more robust a t-distribution than classic purely supervisor models with like LS TNS or cnn's so I think that's starting to get much more well empirically founded than kind