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Differentiable Plasticity: A New Method for Learning to Learn

Neuron image
Differentiable Plasticity is a new machine learning method for training neural networks to change their connection weights adaptively even after training is completed, allowing a form of learning inspired by the lifelong plasticity of biological brains.

Scaling Uber’s Apache Hadoop Distributed File System for Growth

Uber's Data Infrastructure team overhauled our approach to scaling our storage infrastructure by incorporating several new features and functionalities, including ViewFs, NameNode garbage collection tuning, and an HDFS load management service.

Fighting Resistance, Finding Balance: A Conversation with Sophia Vicent, Uber’s Director of Technical Program Management

Sophia Vicent joined Uber after spending 10 years away from the workforce to raise her daughter. We caught up with her to discuss her journey in technical program management.

Building Check-In Queuing & Appointment Scheduling for In-Person Support at Uber

Uber's Customer Obsession Engineering team developed new check-in queuing and appointment systems to improve the customer experience for driver-partners at our Greenlight Hubs.

Open Source at Uber: A Conversation with Nicolas Garcia Belmonte, Head of Visualization

Nicolas Garcia Belmonte
Nicolas Garcia Belmonte, head of visualization, talks about his experience getting started in open source and the role it plays in his work at Uber.

Introducing QALM, Uber’s QoS Load Management Framework

Uber Engineering built QALM, a smart load management tool allowing for graceful degradation by preserving critical system requests and shedding non-critical requests.

VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution

Uber AI Labs introduces Visual Inspector for Neuroevolution (VINE), an open source interactive data visualization tool to help neuroevolution researchers better understand this family of algorithms.

Out of the Arcade: Designing the Uber Kiosk

Uber kiosks in the mall
The design of Uber's driver support kiosk drew inspiration from arcade games of the past along with new thinking on how to engage with customers in public spaces.

Scaling Infrastructure Management with Grail

Uber Engineering built Grail, our infrastructure management platform, to aggregate the current state of our systems into a single global view, spanning all zones and regions.

From Milking Cows to Writing Code: A Dreamer’s Journey

Benito Sanchez at work
Brought to the US when he was 10 years old, DACA gave Benito Sanchez the security to go to college and get a job in technology.

Celebrating Uber Bangalore’s Women in Tech

In honor of International Women’s Day (March 8), Disha Pancholi, Uber Bangalore Engineering’s Site Program Manager, sat down with members of her office to discuss their experiences as women in technology.

Queryparser, an Open Source Tool for Parsing and Analyzing SQL

Written in Haskell, Queryparser is Uber Engineering's open source tool for parsing and analyzing SQL queries that makes it easy to identify foreign-key relationships in large data warehouses.

Scalable Systems & Scalable Careers: A Chat with Uber’s Sumbry

What do Site Reliability Engineering (SRE) and mentorship have in common? According to Uber SRE manager Sumbry, both areas focus on growth.

Code Migration in Production: Rewriting the Sharding Layer of Uber’s Schemaless Datastore

Migrating our Schemaless sharding layer from Python to Go while in production demonstrated that it was possible for us to rewrite the frontend of a massive datastore with zero downtime.

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.

Building Reliable Reprocessing and Dead Letter Queues with Apache Kafka

The Uber Insurance Engineering team extended Kafka’s role in our existing event-driven architecture by using non-blocking request reprocessing and dead letter queues (DLQ) to achieve decoupled, observable error-handling without disrupting real-time traffic.

Implementing Model-Agnosticism in Uber’s Real-Time Anomaly Detection Platform

Uber Engineering extended our anomaly detection platform's ability to integrate new forecast models, allowing this critical on-call service to scale to meet more complex use cases.

Designing Uber’s Product Manager Bootcamp

Uber’s Product Manager Bootcamp facilitates a more robust and streamlined onboarding experience for new PMs, leading to increased alignment, communication, and collaboration between product teams.

Meet Uber’s Software Engineer Apprentices

Uber's Software Engineer Apprentice Program gives developers with non-traditional paths to programming an opportunity to work on industry-level software while receiving extended training and mentorship.

NEAL, Uber’s Open Source Language-Agnostic Linting Platform

Not Exactly a Linter (NEAL) takes code reviews one step closer to full automation by allowing engineers to write custom syntax-based rules in any language.

Omphalos, Uber’s Parallel and Language-Extensible Time Series Backtesting Tool

Uber Engineering created Omphalos, our new backtesting framework, to enable efficient and reliable comparison of forecasting models across languages.

Playing the Perfect Game: Building Uber Eats on Android

To mark the two-year anniversary of Uber Eats, Android engineer Hilary Karls discusses how her team's commitment to "playing the perfect game" resulted in one of Uber’s most successful products.

SBNet: Leveraging Activation Block Sparsity for Speeding up Convolutional Neural Networks

Uber ATG Toronto developed Sparse Blocks Network (SBNet), an open source algorithm for TensorFlow, to speed up inference of our 3D vehicle detection systems while lowering computational costs.

Harnessing Code Generation to Increase Reliability & Productivity on iOS at Uber

Uber's mobile engineers leverage code generation to make our applications more reliable and boost developer productivity.

Engineering Confidence: A Beginner’s Guide to Overcoming Imposter Syndrome

How do you overcome imposter syndrome? Act with confidence, follow your first instinct, and always be learning and teaching.

COTA: Improving Uber Customer Care with NLP & Machine Learning

In this article, Uber Engineering introduces our Customer Obsession Ticket Assistant (COTA), a new tool that puts machine learning and natural language processing models in the service of customer care to help agents deliver improved support experiences.

Architects of Infrastructure: Meet Uber Aarhus Engineering

Get to know Uber Aarhus Engineering and the work they do behind the scenes to build and maintain our storage and compute platforms.

Year in Review: 2017 Highlights from Uber Open Source

As we approach the New Year, Uber Open Source revisits some of Uber Engineering's most popular projects from 2017.

Year in Review: 2017 Highlights from the Uber Engineering Blog

To ring in the New Year, the Uber Engineering Blog shares some of our editor's picks for 2017.

Welcoming the Era of Deep Neuroevolution

By leveraging neuroevolution to train deep neural networks, Uber AI Labs is developing solutions to solve reinforcement learning problems.

Unifying Mobile Onboarding Experiences at Uber

By unifying mobile onboarding experiences for our new rider app, Uber Engineering made it easier than ever before for users to "get moving."

Navigating the Engineering Interview Process at Uber & Beyond

Up for the challenge of developing at unprecedented scale? First, learn what it takes to master the technical interview process at Uber.

Gleaning Insights from Uber’s Partner Activity Matrix with Genomic Biclustering and Machine Learning

Uber Engineering's partner activity matrix leverages biclustering and machine learning to better understand the diversity of user experiences on our driver app.

Denial By DNS: Uber’s Open Source Tool for Preventing Resource Exhaustion by DNS Outages

Uber Engineering built Denial by DNS, our open source solution for preventing DoS by DNS outages, to facilitate more reliable experiences on Uber's apps, no matter how users choose to access them.

Reliability at Scale: Engineering an Uneventful New Year’s Eve

How does Uber keep New Year's Eve and other high traffic events...well, uneventful? By keeping our networks extensible and our services reliable year-round.

Architecting Uber Support with Customer Obsession Engineering

Uber’s Customer Obsession team builds tools that make the customer support experience quicker and more seamless for users across our services.

Welcoming Peter Dayan to Uber AI Labs

Arriving now: Uber's Chief Scientist Zoubin Ghahramani introduces Uber AI Labs' newest team member, award-winning neuroscientist Peter Dayan.

Engineering More Reliable Transportation with Machine Learning and AI at Uber

In this article, we highlight how Uber leverages machine learning and artificial intelligence to tackle engineering challenges at scale.

Uber AI Labs Open Sources Pyro, a Deep Probabilistic Programming Language

Pyro is an open source probabilistic programming language that unites modern deep learning with Bayesian modeling for a tool-first approach to AI.

Engineering Uber’s On-Call Dashboard

Uber Engineering's On-Call Dashboard provides real-time incident response, shift maintenance, and post-mortem analysis for an improved on-call experience.

Turbocharging Analytics at Uber with our Data Science Workbench

Uber Engineering's data science workbench (DSW) is an all-in-one toolbox that leverages aggregate data for interactive analytics and machine learning.

Scaling Reliable Transportation for India: Meet Uber Bangalore Engineering

In this article, members of Uber Bangalore Engineering discuss their role in building reliable transportation systems at scale for India—and beyond.

Engineering NullAway, Uber’s Open Source Tool for Detecting NullPointerExceptions on Android

Uber Engineering built and open sourced NullAway, our fast and practical tool for eliminating NPEs, to help others deploy more reliable Android apps.

Meet Horovod: Uber’s Open Source Distributed Deep Learning Framework for TensorFlow

Uber Engineering introduces Horovod, an open source framework that makes it faster and easier to train deep learning models with TensorFlow.

Introducing AthenaX, Uber Engineering’s Open Source Streaming Analytics Platform

Uber Engineering built AthenaX, our open source streaming analytics platform, to bring large-scale event stream processing to everyone.

Engineering a Million-Mile Journey with Uber ATG

Uber ATG's Poornima Kaniarasu shares how she found her "place" developing the machine learning technologies behind our self-driving vehicles.

How to Have Your Software Engineering Job and Eat It Too

Uber Engineering’s Aimee Lucido reflects on how she redefined her career as a software engineer through advocacy and writing.

Engineering Restaurant Manager, our UberEATS Analytics Dashboard

The UberEATS Restaurant Manager gives restaurant partners insight into their business by measuring customer satisfaction, sales, and service quality.

My Site Reliability Engineering Internship Experience with Uber

What did you do this summer? In this article, intern Mitali Palekar reflects on her experience as a member of Uber's Site Reliability Engineering team.

How Uber Engineering’s Roche Janken Channels Creativity into Code

Uber's Roche Janken shares how her background as a dancer influences her approach to privacy engineering.

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