motivation the models that will work best the most powerful models will typically require a large amounts of data so if your data is very limited it might be very difficult to get a very accurate posterior or very accurate estimate of Phi so the problem at its core that we're going to be dealing with a meta learning is how do you do a good job of estimating Phi when your data is limited and the way you're going to do that is by incorporating more data that is not exactly for the tasks that you want but somehow structurally related so