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Designing a Production-Ready Kappa Architecture for Timely Data Stream Processing

We implemented a Kappa architecture at Uber to effectively backfill streaming data at scale, ensuring accurate data in our platform.

Engineering SQL Support on Apache Pinot at Uber

We engineered full SQL support on Apache Pinot to enable quick analysis and reporting on aggregated data, leading to improved experiences on our platform.

Open Sourcing Manifold, a Visual Debugging Tool for Machine Learning

First introduced by Uber Engineering in January 2019, Manifold is a visual debugging tool that enables users to quickly identify performance issues in machine learning models.
San Francisco map showing average, clustered traffic speeds

Uber Visualization Highlights: Displaying City Street Speed Clusters with SpeedsUp

As part of Uber Visualization's all-team hackathon, we built SpeedsUp, a project using machine learning to process average speeds across a city, cluster the results, and overlay them on a street map.
Uber open source logo

Uber Open Source in 2019: Community Engagement and Contributions

Uber recounts its many engagements with the open source community during 2019, from contributing projects to joining and founding new open source support organizations.

Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data

Developed by Uber AI Labs, Generative Teaching Networks (GTNs) automatically generate training data, learning environments, and curricula to help AI agents rapidly learn.

Productionizing Distributed XGBoost to Train Deep Tree Models with Large Data Sets at Uber

We share technical challenges and lessons learned while productionizing and scaling XGBoost to train distributed gradient boosted algorithms at Uber.

Controlling Text Generation with Plug and Play Language Models

Plug and Play Language Model, introduced by Uber AI Labs, gives NLP practitioners the flexibility to plug in one or more simple attribute models into a large, unconditional language model.

Uber Goes to NeurIPS 2019

Uber is presenting 11 papers at the NeurIPS 2019 conference in Vancouver, Canada, as well as sponsoring workshops including Women in Machine Learning (WiML) and Black in AI.
RxCentralBle: Uber's Open Source Library for Seamless Bluetooth Integrations

RxCentral: Uber’s Open Source Library for Seamless Bluetooth Integrations

Uber introduces RxCentral, an open source library to reliably and repeatedly connect Bluetooth devices using a platform-agnostic, reactive design.

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).
Conducting Better Business with Uber's Open Source Orchestration Tool, Cadence

Conducting Better Business with Uber’s Open Source Orchestration Tool, Cadence

Uber engineers describe Cadence, Uber’s open source workflow orchestration tool, its architecture, and its use in a series of informative presentations.

Improving Pickups with Better Location Accuracy

Uber built beacon to improve vehicle location accuracy on our platform, leading to more seamless rider pickup and dropoff experiences.

Taking City Visualization into the Third Dimension with Point Clouds, 3D Tiles, and deck.gl

With the release of deck.gl version 7.3, Uber’s open source visualization tool now supports rendering massive geospatial data sets formatted according to the OGC 3D Tiles community standard.
Uber IT Engineering team

IT Engineering: Meet the Team that Keeps Uber Moving

Uber's IT Engineering team builds the tools and systems that help other Uber employees do their jobs. Meet a few of these remarkable behind-the-scenes engineers.

Evolving Michelangelo Model Representation for Flexibility at Scale

To accommodate additional ML use cases, Uber evolved Michelangelo's application of the Apache Spark MLlib library for greater flexibility and extensibility.

Building a Better Big Data Architecture: Meet Uber’s Presto Team

Uber has embraced Presto, a high performance, distributed SQL query engine, and joined the Presto Foundation. Meet the Uber engineers who contribute to and use Presto on a daily basis.
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.
Thuan Pham and Sudhanshu Mishra

On Internships, Career Advice, and Reaching 15B Rides: A Conversation with Uber CTO Thuan...

CTO Thuan Pham sat down with former intern, now employee, Sudhanshu Mishra to talk about his early experiences in the technology industry and growing Uber.
Dragonfly

Introducing Hypothesis GU Funcs, an Open Source Python Package for Unit Testing

Uber introduces Hypothesis GU Func, a new extension to Hypothesis, as an open source Python package for unit testing.

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