neural networks people would use these between layers all the time and they make sense there that kind of biologically inspired you take any activation you scale it from 0 to 1 or minus 1 to 1 but they're actually really really problematic because if you get a neuron which has a very high activation value then you've got this number up here which is 1 and you take the derivative of that and it's 0 or it's some very very small number and so your gradient descent can't tell the difference between an activation up here