The Future of Machine Learning

In order to build new nets with the kind of a broad knowledge of the world that typical adult humans have, probably the kind of competing power we have now is going to be insufficient. Even our state of the art deep learning methods fail to learn models that understand even very simple environments like gridwolds. And so i think there's an opportunity for academics who don't have the kind of computing power that sagugl has. I'm to do really important and exciting research to advance the state of theArt in training frameworks, learning models,. agent learning in even simple environments that are synthetic, that seem trivial.