There are different ways to assess an open source projects success, but measurable metrics (like pull requests and contributions) typically play some role. One of the challenges Uber has faced involv …

Paco Nathan outlines the history and landscape for vendors, open source projects, and research efforts related to AutoML. Starting from the perspective of an AI expert practitioner who speaks business fluently, Paco unpacks the ground truth of AutoMLtranslating from the hype into business concerns and practices in a vendor-neutral way.

Paco Nathan outlines the history and landscape for vendors, open source projects, and research efforts related to AutoML. Starting from the perspective of an AI expert practitioner who speaks business fluently, Paco unpacks the ground truth of AutoMLtranslating from the hype into business concerns and practices in a vendor-neutral way.

This talk will present in detail the long and windy path that Uber has been on over the past few years to containerize the thousands of microservices written by thousands of engineers.It will go throu …

Uber applies natural language processing (NLP) and conversational AI in a number of business domains. Huaixiu Zheng details how Uber applies deep learning in the domain of NLP and conversational AI. You'll learn how Uber implements AI solutions in a real-world environment, as well as cutting-edge research in end-to-end dialogue systems.

Cadence is an open source workflow platform for building reliable and highly scalable distributed applications. It is applicable to very large set of use cases from infrastructure and ML/Data automati …

Managing large stateful applications is tough. Matt Schallert outlines the challenges of automating stateful systems at scale and details how embracing a declarative approach can ease operation and automation of these systems on orchestrators such as Kubernetes. He then demonstrates how to apply this methodology to different types of stateful workloads.

AI will change how we live in the next 30 years, but it's still currently limited to a small group of companies. In order to scale the impact of AI across the globe, we need to reduce the cost of building AI solutions, but how? Nate Keating explains how to apply lessons learned from other industriesspecifically, the automobile industry, which went through a similar cycle.

Uber started using docker containers at scale in 2015, and has gone through a few generations of cluster management and service discovery technologies. In early 2019, we started working on migration f …

Uber relies on Big Data and ML to make business critical decisions such as pricing, trip ETA, etc. Today, those workloads such as Hive and Spark are running on YARN. To save millions of dollars by eff …

Since launching in 2009, Uber has become the poster child for explosive growth - in revenue, headcount, and operational complexity. This growth has created new challenges for Ubers engineering team a …