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.
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.
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.
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.
Uber Engineering built QALM, a smart load management tool allowing for graceful degradation by preserving critical system requests and shedding non-critical requests.
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.
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.
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.
What do Site Reliability Engineering (SRE) and mentorship have in common? According to Uber SRE manager Sumbry, both areas focus on growth.
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.
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.
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.
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.
Uber Engineering created Omphalos, our new backtesting framework, to enable efficient and reliable comparison of forecasting models across languages.
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.
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.
Uber's mobile engineers leverage code generation to make our applications more reliable and boost developer productivity.
How do you overcome imposter syndrome? Act with confidence, follow your first instinct, and always be learning and teaching.
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.
Get to know Uber Aarhus Engineering and the work they do behind the scenes to build and maintain our storage and compute platforms.
As we approach the New Year, Uber Open Source revisits some of Uber Engineering's most popular projects from 2017.
To ring in the New Year, the Uber Engineering Blog shares some of our editor's picks for 2017.
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.
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.
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.
Uber’s Customer Obsession team builds tools that make the customer support experience quicker and more seamless for users across our services.
In this article, we highlight how Uber leverages machine learning and artificial intelligence to tackle engineering challenges at scale.
Pyro is an open source probabilistic programming language that unites modern deep learning with Bayesian modeling for a tool-first approach to AI.
Uber Engineering's data science workbench (DSW) is an all-in-one toolbox that leverages aggregate data for interactive analytics and machine learning.
In this article, members of Uber Bangalore Engineering discuss their role in building reliable transportation systems at scale for India—and beyond.
Uber Engineering built and open sourced NullAway, our fast and practical tool for eliminating NPEs, to help others deploy more reliable Android apps.
Uber Engineering introduces Horovod, an open source framework that makes it faster and easier to train deep learning models with TensorFlow.
Uber Engineering built AthenaX, our open source streaming analytics platform, to bring large-scale event stream processing to everyone.
Uber Engineering’s Aimee Lucido reflects on how she redefined her career as a software engineer through advocacy and writing.
The UberEATS Restaurant Manager gives restaurant partners insight into their business by measuring customer satisfaction, sales, and service quality.
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.
Uber's Roche Janken shares how her background as a dancer influences her approach to privacy engineering.