Self-driving cars have long been considered the future of transportation, but they’re becoming more present everyday. Uber ATG (Advanced Technologies Group) is at the forefront of this technology, helping bring safe, reliable self-driving vehicles...
Developed by Uber ATG, Neuropod is an abstraction layer that provides a universal interface to run models across any deep learning framework.
Enhanced POET: Open-Ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions
Building upon our existing open-ended learning research, Uber AI released Enhanced POET, a project that incorporates an improved algorithm and allows for more diverse training environments.
In October 2019, Uber hosted our second annual Moving The World With Data meetup, showcasing some of our most interesting data science challenges in 2019.
By integrating graph learning techniques with our Uber Eats recommendation system, we created a more seamless and individualized user experience for eaters on our platform.
At an April 2019 meetup on ML and AI at Uber Seattle, members of our engineering team discussed three different approaches to enhancing our ML ecosystem.
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.
The Plato Research Dialogue System enables experts and non-experts alike to quickly build, train, and deploy conversational AI agents.
As head of Uber's Advanced Technologies Center in Paris, Francois Sillion and his team are responsible for supporting the R&D behind Uber Air, our effort to add a third dimension to our platform using flying vehicles.
Uber's Marketplace simulation platform leverages ML to rapidly prototype and test new product features and hypotheses in a risk-free environment.
Uber builds upon the Lottery Ticket Hypothesis by proposing explanations behind these mechanisms and deriving a surprising by-product: the Supermask.
We spoke to Data Science Director Fran Bell about machine learning at Uber and what she finds most challenging—and rewarding—about her work.
Horovod adds support for more frameworks in the latest release and introduces new features to improve versatility and productivity.
Created by Uber in 2017, Pyro was voted in by the Linux Foundation Deep Learning Technical Board as the latest incubation project to join its foundation.
We spoke with Fritz Obermeyer and Noah Goodman, Pyro project co-leads, about the potential of open source AI software at Uber and beyond.
Uber AI developed Ludwig, a code-free deep learning toolbox, to make deep learning more accessible to non-experts and enable faster model iteration cycles.