AI Is About to Learn More Like Humans--with a Little Uncertainty

At Whetlab, a startup acquired by Twitter in 2015, the technique provided a better way of--wait for it--designing neural networks. Designing a neural network is a task of extreme trial and error. It's a difficult and time-consuming undertaking, but GPs and Bayesian optimization can help automate the task. As WhetLab founder and Harvard computer scientist Ryan Adams has said, the startup used "machine learning to improve machine learning." Neural networks can suffer from the "confident error" problem, and in identifying uncertainty, this kind of optimization can help address that problem.