Uber ATG Toronto developed Sparse Blocks Network (SBNet), an open source algorithm for TensorFlow, to speed up inference of our 3D vehicle detection systems while lowering computational costs.
To ring in the New Year, the Uber Engineering Blog shares some of our editor's picks for 2017.
In this article, we highlight how Uber leverages machine learning and artificial intelligence to tackle engineering challenges at scale.
Uber Engineering introduces a new Bayesian neural network architecture that more accurately forecasts time series predictions and uncertainty estimations.
Recurrent neural networks equip Uber Engineering's new forecasting model to more accurately predict rider demand during extreme events.