here and try to predict the other one and you do it vice versa so you get too lost components each time it's a symmetric loss okay and that's it that's the method and they beat all the other self supervised methods and they get pretty close to the supervised supervised representation learning method as you can see right here as the number of parameters goes up in their model so one of them is resonate 50 but I'm gonna guess this one right here but you can also get to higher architectures and then it appears to work even better