Tag: artificial intelligence
Science at Uber: Improving Transportation with Artificial Intelligence
Uber Chief Scientist Zoubin Ghahramani explains how artificial intelligence went from academia to real-world applications, and how Uber uses it to make transportation better.
Three Approaches to Scaling Machine Learning with Uber Seattle Engineering
At an April 2019 meetup on ML and AI at Uber Seattle, members of our engineering team discussed three different approaches to enhancing our ML ecosystem.
Introducing LCA: Loss Change Allocation for Neural Network Training
Uber AI Labs proposes Loss Change Allocation (LCA), a new method that provides a rich window into the neural network training process.
Advancing AI: A Conversation with Jeff Clune, Senior Research Manager at Uber
We sat down with Jeff Clune, Senior Research Manager, to talk about his work in AI, journey to Uber, and Presidential Early Career Achievement in Science and Engineering (PECASE) award.
Science at Uber: Applying Artificial Intelligence at Uber
Zoubin Ghahramani, Head of Uber AI, discusses how we use artificial intelligence techniques to make our platform more efficient for users.
Introducing the Plato Research Dialogue System: A Flexible Conversational AI Platform
The Plato Research Dialogue System enables experts and non-experts alike to quickly build, train, and deploy conversational AI agents.
Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask
Uber builds upon the Lottery Ticket Hypothesis by proposing explanations behind these mechanisms and deriving a surprising by-product: the Supermask.
Introducing the Uber Research Publications Site
Uber's Chief Scientist announces the launch of the Uber Research Publications Site, a portal for showcasing our contributions to the research community.
Data Science at Scale: A Conversation with Uber’s Fran Bell
We spoke to Data Science Director Fran Bell about machine learning at Uber and what she finds most challenging—and rewarding—about her work.
Horovod Adds Support for PySpark and Apache MXNet and Additional Features for Faster Training
Horovod adds support for more frameworks in the latest release and introduces new features to improve versatility and productivity.
Pyro Accepted by the LF Deep Learning Foundation as a Hosted Project
Created by Uber in 2017, Pyro was voted in by the Linux Foundation Deep Learning Technical Board as the latest incubation project to join its foundation.
Uber Open Source: Catching Up with Fritz Obermeyer and Noah Goodman from the Pyro...
We spoke with Fritz Obermeyer and Noah Goodman, Pyro project co-leads, about the potential of open source AI software at Uber and beyond.
First Uber Science Symposium: Discussing the Next Generation of RL, NLP, ConvAI, and DL
The Uber Science Symposium featured talks from members of the broader scientific community about the the latest innovations in RL, NLP, and other fields.
Introducing Ludwig, a Code-Free Deep Learning Toolbox
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.
Creating a Zoo of Atari-Playing Agents to Catalyze the Understanding of Deep Reinforcement Learning
Uber AI Labs releases Atari Model Zoo, an open source repository of both trained Atari Learning Environment agents and tools to better understand them.
POET: Endlessly Generating Increasingly Complex and Diverse Learning Environments and their Solutions through the...
Uber AI Labs introduces the Paired Open-Ended Trailblazer (POET), an algorithm that leverages open-endedness to push the bounds of machine learning.
Women in Data Science at Uber: Moving the World With Data
During an October 2018 meetup, members of our Women in Statistics, Data, Optimization, and Machine Learning (WiSDOM) group presented on their technical work at Uber.
Horovod Joins the LF Deep Learning Foundation as its Newest Project
Horovod, Uber's distributed training framework, joins the LF Deep Learning Foundation to help advance open source innovation in AI, ML, and deep learning.
Open Source at Uber: Meet Alex Sergeev, Horovod Project Lead
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.
Faster Neural Networks Straight from JPEG
Uber AI Labs introduces a method for making neural networks that process images faster and more accurately by leveraging JPEG representations.
