DeepMind et al Paper Trumpets Graph Networks – SyncedReview – Medium

The paper Relational inductive biases, deep learning, and graph networks, published last week on arXiv by researchers from DeepMind, Google Brain, MIT and University of Edinburgh, has stimulated discussion in the artificial intelligence community. The paper introduces a new machine learning framework called Graph Networks, which some believe promises huge potential for approaching the holy grail of artificial general intelligence. Due to the development of big data and increasingly powerful computational resources over the past few years, modern AI technology -- primarily deep learning -- has show its prowess and even outsmarted humans in tasks such as image recognition and speech detection. However, AI remains challenged by tasks that involve complicated learning and reasoning with limited experience and knowledge, which is exactly what humans are good at. Although "a word to the wise is sufficient," machines require much more.