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Tag: Uber ATG

Profiles in Coding: Diana Yanakiev, Uber ATG, Pittsburgh

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...

Introducing Neuropod, Uber ATG’s Open Source Deep Learning Inference Engine

Developed by Uber ATG, Neuropod is an abstraction layer that provides a universal interface to run models across any deep learning framework.

Inside Uber ATG’s Data Mining Operation: Identifying Real Road Scenarios at Scale for Machine...

Uber ATG's self-driving vehicles measure a multitude of possible scenario variations to answer the age-old question: "how does the pedestrian cross the road?"

Introducing Athenadriver: An Open Source Amazon Athena Database Driver for Go

Uber ATG built Athenadriver, an open source Amazon Athena database driver for Go, to facilitate communication between our business intelligence tools and the cloud.

Celebrating International Women’s Day: Meet the Women Building Uber’s Global Platform

To celebrate International Women's Day, we spoke with women from across the company whose work helps deliver impactful experiences for Uber users worldwide.
Uber ATG self-driving cars

Under the Hood of Uber ATG’s Machine Learning Infrastructure and Versioning Control Platform for...

Managing multiple machine learning models to enable self-driving vehicles is a challenge. Uber ATG developed a model life cycle for quick iterations and a tool for continuous delivery and dependency management.

Announcing the 2020 Uber AI Residency

Uber's 2020 AI Residency will focus on initiatives related to our self-driving car project through Uber Advanced Technology Group (ATG).
Ski lift on snowy mountain

Global Tech in the Great Outdoors: Meet Uber’s Boulder Tech Office

Meet a few of the engineers from Uber's Boulder, Colorado office, working on everything from maps to new mobility to large-scale distributed systems.
Pedestrian density map

Searchable Ground Truth: Querying Uncommon Scenarios in Self-Driving Car Development

When developing Uber's self driving car systems, engineers found a way to identify edge case scenarios amongst terabytes of sensor data representing real-world situations.

Best Practices for Unit Testing in React Version 16

Uber ATG Web Platform intern Anat Kleiman shares her advice for testing React version 16 components when altering application logic.

Solving for Urban Air Travel: A Q&A with François Sillion, Director of Uber ATCP

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.

Power On: Accelerating Uber’s Self-Driving Vehicle Development with Data

A key challenge faced by self-driving vehicles comes during interactions with pedestrians. In our development of self-driving vehicles, the Data Engineering and Data Science teams at Uber ATG (Advanced Technologies Group) contribute to the data processing and analysis that help make these interactions safe.
Rendered image of street and vehicles

Introducing AVS, an Open Standard for Autonomous Vehicle Visualization from Uber

Uber announces the release of the Autonomous Visualization System (AVS) as an open source project. AVS is a standard for creating a visual environment based on sensor data from autonomous vehicles, with playback available in multiple formats, including the web and video.

From Self-Driving Cars to Optimizing Claims Efficiency: My Unconventional Journey to Insurance Engineering

In this article, engineering manager Lili Kan reflects on her decision to lead Uber's Insurance Engineering team and discusses the challenges—and opportunities—of building insurance products for our platform.

Four Ways Uber Visualization Made an Impact in 2018

Uber's Head of Urban Computing & Visualization reflects on his team's work visualizing data to better understand urban mobility in 2018—and beyond.

Open Source at Uber: Meet Alex Sergeev, Horovod Project Lead

We sat down with Horovod project lead, Alex Sergeev, to discuss his path to open source and what most excites him about the future of Uber's distributed deep learning framework.

Announcing the 2019 Uber AI Residency

The Uber AI Residency is a 12-month training program for academics and professionals interested in becoming an AI researcher with Uber AI Labs or Uber ATG.

Scaling Machine Learning at Uber with Michelangelo

Uber built Michelangelo, our machine learning platform, in 2015. Three years later, we reflect our journey to scaling ML at Uber and lessons learned along the way.

Going Global: Highlights from the Second Annual Uber Technology Day

On April 19, 2018, Uber's LadyEng group hosted Going Global: Uber Tech Day, our second annual event focused on showcasing the technical work of engineers, data scientists, and product managers from across the company.

Introducing the Uber AI Residency

Interested in accelerating your career by tackling some of Uber’s most challenging AI problems? Apply for the Uber AI Residency, a research fellowship dedicated to fostering the next generation of AI talent.

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