Connecting the digital and physical worlds safely and reliably on the Uber platform presents exciting technological challenges and opportunities. For Uber, artificial intelligence (AI) is essential to developing systems that are capable of optimized, automated decision making at scale.
AI …
The post Announcing the 2020 Uber AI Residency appeared first on Uber Engineering Blog.
Uber ATG is committed to publishing research advancements with the goal of bringing self-driving cars to the world safely and scalably. We hope our approach to sharing will deepen the interactions and collaborations between industry and academia, and will ultimately …
The post Get to Know Uber ATG at ICCV, CoRL, and IROS 2019 appeared first on Uber Engineering Blog.
Michelangelo, Uber’s machine learning (ML) platform, supports the training and serving of thousands of models in production across the company. Designed to cover the end-to-end ML workflow, the system currently supports classical machine learning, time series forecasting, and deep …
The post Evolving Michelangelo Model Representation for Flexibility at Scale appeared first on Uber Engineering Blog.
At Uber ATG, developing a safe self-driving car system not only means training it on the typical traffic scenarios we see every day, but also the edge cases, those more difficult and rare situations that would even flummox a human …
The post Searchable Ground Truth: Querying Uncommon Scenarios in Self-Driving Car Development appeared first on Uber Engineering Blog.
At Uber, we take advanced research work and use it to solve real world problems. In our Science at Uber video series, Uber employees talk about how we apply data science, artificial intelligence, machine learning, and other innovative technologies …
The post Science at Uber: Improving Transportation with Artificial Intelligence appeared first on Uber Engineering Blog.
Uber’s services require real-world coordination between a wide range of customers, including driver-partners, riders, restaurants, and eaters. Accurately forecasting things like rider demand and ETAs enables this coordination, which makes our services work as seamlessly as possible.
In an effort …
The post Three Approaches to Scaling Machine Learning with Uber Seattle Engineering appeared first on Uber Engineering Blog.
At Uber, we take advanced research work and use it to solve real world problems. In our Science at Uber video series, Uber employees talk about how we apply data science, artificial intelligence, machine learning, and other innovative technologies …
The post Science at Uber: Powering Machine Learning at Uber appeared first on Uber Engineering Blog.
Neural networks (NNs) have become prolific over the last decade and now power machine learning across the industry. At Uber, we use NNs for a variety of purposes, including detecting and predicting object motion for self-driving vehicles, responding more …
The post Introducing LCA: Loss Change Allocation for Neural Network Training appeared first on Uber Engineering Blog.
The past few months have been a whirlwind for Jeff Clune, Senior Research Manager at Uber and a founding member of Uber AI Labs. In June 2019, research by him and his collaborators on POET, an algorithm …
The post Advancing AI: A Conversation with Jeff Clune, Senior Research Manager at Uber appeared first on Uber Engineering Blog.
At Uber, we take advanced research work and use it to solve real world problems. In our Science at Uber video series, Uber employees talk about how we apply data science, artificial intelligence, machine learning, and other innovative technologies …
The post Science at Uber: Applying Artificial Intelligence at Uber appeared first on Uber Engineering Blog.
