being able to learn from small amounts of data and in particular what we've seen is that meta learning thrives with large data sets if there's one thing to take away from the last few years of machine learning research I think it's that large diverse data sets plus large models leads to broad generalization we've seen this time and time again from systems trained on imagenet to transform our models trained on large machine translation systems to GPT to trained for large-scale language modeling and all this falls under the paradigm of