Uber AI is the research and platform team for everything AI at the company with the exception of self-driving cars. Self-driving cars are left to Uber ATG. Ludwig allows you to specify a Tensorflow model in a declarative format that focuses on your inputs and outputs. Ludwig then builds a model that can deal with those types of inputs and outputs without a developer explicitly specifying how that is done. Because of Ludwig's datatype abstraction for inputs and outputs, there is a huge range of applications that can be created.

We have been developing Ludwig internally at Uber over the past two years to streamline and simplify the use of deep learning models in applied projects, as they usually require comparisons among different architectures and fast iteration. We have witnessed its value to several of Uber's own projects, including our Customer Obsession Ticket Assistant (COTA), information extraction from driver licenses, identification of points of interest during conversations between driver-partners and riders, food delivery time prediction, and much more. For this reason we decided to release it as open source, as we believe there is no other solution currently available with the same ease of use and flexibility.