parameters of of another neural network this doesn't really seem scalable but if the the the neural network that's making inferences about test data points has millions of parameters then we need a neural network that outputs millions of a million million dimensional output and one idea that we can use to remedy this is we don't actually need to output all of the parameters of another neural network we really just need to output the sufficient statistics of that data set of the training tasks that allow us to make predictions about new data