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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.

Uber Visualization Highlights: Displaying City Street Speed Clusters with SpeedsUp

San Francisco map showing average, clustered traffic speeds
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 in 2019: Community Engagement and Contributions

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

Year in Review: 2019 Highlights from the Uber Engineering Blog

To cap off 2019, the Uber Engineering Blog editors present a selection of our most popular articles covering a range of technical topics, from AI to mobile development.

Uber Infrastructure in 2019: Improving Reliability, Driving Customer Satisfaction

In 2019, Uber's Infrastructure team built new services and systems to enable resource savings, efficiency gains, and greater resilience across our technology stack.

Uber AI in 2019: Advancing Mobility with Artificial Intelligence

In 2019, Uber AI built tools and systems that leverage ML to improve location accuracy and enhance real-time forecasting, among other applications on our platform.

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.

Uber’s Data Platform in 2019: Transforming Information to Intelligence

In 2019, Uber's Data Platform team leveraged data science to improve the efficiency of our infrastructure, enabling us to compute optimum datastore and hardware usage.

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.

Food Discovery with Uber Eats: Using Graph Learning to Power Recommendations

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.

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.

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

RxCentralBle: 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).

Optimizing Observability with Jaeger, M3, and XYS at Uber

Uber’s observability engineers present their work on distributed tracing (Jaeger), sampling (XYS), and metrics processing (M3).

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

Ski lift on snowy mountain
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.

Uber Visualization Highlights: How Urban Symphony Adds an Audio Dimension to Visualization

As part of Uber Visualization's all-team hackathon, we built Urban Symphony, an Uber Movement visualization that adds an audio component to traffic speed patterns.

Introducing Menu Maker: Uber Eats’ New Menu Management Tool

To simplify the Uber Eats experience for our restaurant-partners, we built Menu Maker, a web-based tool for seamlessly managing menus on the Uber Eats app.

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.

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