2055 results for "receipt" across all locations
Tell us the destination you’ve been dreaming of for a chance to go there—on us
We’re giving 2 lucky riders roundtrip flights to anywhere in the world. Just look for the “Where To” sign when you ride and follow the steps to enter.
Inclusion Matters: Access and Empowerment for Riders and Drivers with Disability in Australia
Uber is continuing to increase mobility options for riders with disability by working hard to provide inclusive access to safe, reliable and affordable door to door transport. Uber is also highlighting the flexible and well paid nature of ridesharing, which provides much needed economic opportunities to the disabled community.
Discover the work Uber has been doing to improve our accessibility for both riders and drivers with disability in Australia.
Uber Eats at SoFi Stadium
In 2023, fans at select Live Nation amphitheaters can order food and beverages for fast pickup directly from the Uber Eats app. When inside select Live Nation venues, you can open your Uber Eats app, select the area you’re in, and you will be shown all available merchants you can order from. When the order is ready, you will receive a notification to skip the line and pick it up, so you don’t have to spend time waiting in lines and risk missing a set.
Uber Phoenix adds rider assistance and wheelchair accessible vehicles with uberACCESS
Uber has evolved the way people move throughout Phoenix and more than 300 other cities around the world. Until recently, transportation options have been limited for the more than 200,000 Phoenicians with disabilities who may require a ramp or a lift for additional assistance. Uber Phoenix is introducing a new platform that allows those needing an extra hand, or even access to wheelchair accessible vehicles, to request safe and reliable rides with uberACCESS; a separate vehicle view that lets riders with specific needs request two different vehicle types at the tap of a button.
Fiber: A Platform for Efficient Development and Distributed Training for Reinforcement Learning and Population-Based Methods
J. Zhi, R. Wang, J. Clune, K. Stanley
Recent advances in machine learning are consistently enabled by increasing amounts of computation. Reinforcement learning (RL) and population-based methods in particular pose unique challenges for efficiency and flexibility to the underlying distributed computing frameworks. These challenges include frequent interaction with simulations, the need for dynamic scaling, and the need for a user interface with low adoption cost and consistency across different backends. In this paper we address these challenges while still retaining development efficiency and flexibility for both research and practical applications by introducing Fiber, a scalable distributed computing framework for RL and population-based methods. […] [PDF]
arXiv
Your questions, our answers
Following TfL’s announcement that it would not be renewing Uber London’s licence, many of you have questions about your future with us.
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