Newall networks that's more basic transfer learning can you talk about the difference between the big general meta learning and a more narrow sense of meta learning the way it's used today the ways talked about today let's take the example of a deep neural networks that has learnt to classify images and maybe you have trained that network on 100 different databases of images and now a new database comes along and you want to quickly learn the new thing as well so one simple way of doing that as you take the network which already knows 100