Uber launches Beacon V2, a piece of hardware for Uber drivers, that implements on-device sensor fusion using signals from GNSS, IMU, and barometer to improve location accuracy.

We publish our research results to the broader scientific community. This year, Uber is presenting 11 papers at the NeurIPS 2019 conference! We are also sponsoring WiML and Black in AI.

We develop a new measure called Loss Change Allocation (LCA) to better understand the training process. LCA measures how much each parameter helps decrease (or increase) the loss at every iteration. It is able to reveal broader patterns such as how training is very noisy, some layers hurt, and micro-learning is synchronized across layers.

Ludwig 0.2 is released with a host of new functionalities and features. The major ones are the integration with Comet.ml, the addition of BERT among text encoders, the implementation of audio/ speech, H3 (geospatial) and date (temporal) features, substantial improvements on the visualization API, and the inclusion of a serving functionality.

Uber AI Labs releases EvoGrad, a library for catalyzing gradient-based evolution research, and Evolvability ES, a new meta-learning algorithm enabled by this library.

Plato Research Dialogue System is a platform for building, training, and deploying conversational AI agents that allows us to conduct state of the art research in conversational AI and quickly create prototypes and demonstration systems, as well as facilitate conversational data collection.

Uber builds upon the Lottery Ticket Hypothesis by proposing explanations behind these mechanisms and deriving a surprising by-product: the Supermask.

Uber's Chief Scientist announces the launch of the Uber Research Publications Site, a portal for showcasing our contributions to the research community.