We spoke with Fritz Obermeyer and Noah Goodman, Pyro project co-leads, about the potential of open source AI software at Uber and beyond.
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.
Censored time-to-event data is critical to the proper modeling and understanding of customer engagement on the Uber platform. In this article, we demonstrate an easier way to model this data using Pyro.
Uber AI developed Ludwig, a code-free deep learning toolbox, to make deep learning more accessible to non-experts and enable faster model iteration cycles.
AresDB, Uber's open source real-time analytics engine, leverages GPUs to enable real-time computation and data processing in parallel.
Brian Hsieh, Uber's Open Source program lead, reflects on open source accomplishments, project launches, and collaborations in 2018.
Horovod, Uber's distributed training framework, joins the LF Deep Learning Foundation to help advance open source innovation in AI, ML, and deep learning.
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.
Uber built Makisu, our open source Docker image builder, to enable the quick, reliable generation of Dockerfiles in Mesos and Kubernetes ecosystems.
As part of the OpenChain Project’s governing board, Uber will help create best practices and define standards for open source software compliance.
Uber hosted its first Open Summit on November 15, inviting the open source community to learn about our open source projects from the engineers who use them every day. Check out highlights from the day, including keynotes from the Linux Foundation's Jim Zemlin and Uber AI's Zoubin Ghahramani.
In our continuing series about building our new driver app, Uber engineers discuss designing the architecture of the mobile app using RIBs, our open source mobile development framework.
Uber open source projects leads give updates on seven of our projects, all of which will be showcased at the upcoming Uber Open Summit 2018.
Yuri Shkuro dicusses his journey to open source at Uber, his experience developing Jaeger, our open source distributed tracing system, and how to grow an open source community from scratch.
Keynote speakers include Jim Zemlin, executive director of the Linux Foundation, and Zoubin Ghahramani, chief scientist at Uber AI Labs.
Uber's Advanced Technologies Group introduces Petastorm, an open source data access library enabling training and evaluation of deep learning models directly from multi-terabyte datasets in Apache Parquet format.
Today we introduce Marmaray, an open source framework allowing data ingestion and dispersal for Apache Hadoop, realizing our vision of any-sync-to-any-source functionality, including data format validation.
M3, Uber's open source metrics platform for Prometheus, facilitates scalable and configurable multi-tenant storage for large-scale metrics.
Fusion.js, Uber's new open source web framework, supports modern features and integrations that make it easy to build lightweight, high-performing apps for the web.
Uber open sourced JVM Profiler, our distributed profiler, to enable others to seamlessly collect JVM performance and resource usage metrics.