Uber AI

Uber AI is at the heart of AI-powered innovation and technologies at Uber. AI research and its applications solve challenges across the whole of Uber.

Uber AI, Engineering

Ludwig v0.2 Adds New Features and Other Improvements to its Deep Learning Toolbox

July 24, 2019 / Global

Uber AI

Introducing EvoGrad: A Lightweight Library for Gradient-Based Evolution

July 22, 2019 / Global

Uber AI

Introducing the Plato Research Dialogue System: A Flexible Conversational AI Platform

July 16, 2019 / Global

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Stay up to date with the latest from Uber Engineering

Uber AI, Data / ML

Gaining Insights in a Simulated Marketplace with Machine Learning at Uber

June 24, 2019 / Global

Uber AI, Engineering

No Coding Required: Training Models with Ludwig, Uber’s Open Source Deep Learning Toolbox

June 14, 2019 / Global

Engineering, Uber AI

Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask

May 6, 2019 / Global

Uber AI

Accessible Machine Learning through Data Workflow Management

March 18, 2019 / Global

Uber AI, Engineering

Horovod Adds Support for PySpark and Apache MXNet and Additional Features for Faster Training

February 21, 2019 / Global

Uber AI, Engineering

Uber Open Source: Catching Up with Fritz Obermeyer and Noah Goodman from the Pyro Team

February 21, 2019 / Global

Uber AI, Engineering

Modeling Censored Time-to-Event Data Using Pyro, an Open Source Probabilistic Programming Language

February 15, 2019 / Global

Uber AI, Culture

First Uber Science Symposium: Discussing the Next Generation of RL, NLP, ConvAI, and DL

February 12, 2019 / Global

Uber AI, Engineering

Introducing Ludwig, a Code-Free Deep Learning Toolbox

February 11, 2019 / Global

Uber AI, Data / ML

Manifold: A Model-Agnostic Visual Debugging Tool for Machine Learning at Uber

January 14, 2019 / Global

Uber AI

Creating a Zoo of Atari-Playing Agents to Catalyze the Understanding of Deep Reinforcement Learning

January 9, 2019 / Global

Uber AI

POET: Endlessly Generating Increasingly Complex and Diverse Learning Environments and their Solutions through the Paired Open-Ended Trailblazer

January 8, 2019 / Global

Engineering, Uber AI

Faster Neural Networks Straight from JPEG

December 11, 2018 / Global

Engineering, Uber AI

Uber AI

Ludwig v0.2 Adds New Features and Other Improvements to its Deep Learning Toolbox

Introducing EvoGrad: A Lightweight Library for Gradient-Based Evolution

Introducing the Plato Research Dialogue System: A Flexible Conversational AI Platform

Interested in joining Uber Eng?

Stay up to date with the latest from Uber Engineering

Gaining Insights in a Simulated Marketplace with Machine Learning at Uber

No Coding Required: Training Models with Ludwig, Uber’s Open Source Deep Learning Toolbox

Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask

Accessible Machine Learning through Data Workflow Management

Horovod Adds Support for PySpark and Apache MXNet and Additional Features for Faster Training

Uber Open Source: Catching Up with Fritz Obermeyer and Noah Goodman from the Pyro Team

Modeling Censored Time-to-Event Data Using Pyro, an Open Source Probabilistic Programming Language

First Uber Science Symposium: Discussing the Next Generation of RL, NLP, ConvAI, and DL

Introducing Ludwig, a Code-Free Deep Learning Toolbox

Manifold: A Model-Agnostic Visual Debugging Tool for Machine Learning at Uber

Creating a Zoo of Atari-Playing Agents to Catalyze the Understanding of Deep Reinforcement Learning

POET: Endlessly Generating Increasingly Complex and Diverse Learning Environments and their Solutions through the Paired Open-Ended Trailblazer

Faster Neural Networks Straight from JPEG

How to Get a Better GAN (Almost) for Free: Introducing the Metropolis-Hastings GAN

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