Tag: artificial intelligence

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.

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

Metropolis-Hastings Generative Adversarial Networks (GANs) leverage the discriminator to pick better samples from the generator after ML model training is done.

Montezuma’s Revenge Solved by Go-Explore, a New Algorithm for Hard-Exploration Problems (Sets Records on...

Uber AI Labs introduces Go-Explore, a new reinforcement learning algorithm for solving a variety of challenging problems, especially in robotics.

Announcing the 2019 Uber AI Residency

The Uber AI Residency is a 12-month training program for academics and professionals interested in becoming an AI researcher with Uber AI Labs or Uber ATG.
Photo of Uber app showing map

Applying Customer Feedback: How NLP & Deep Learning Improve Uber’s Maps

To improve our maps, Uber Engineering analyzes customer support tickets with natural language processing and deep learning to identify and correct inaccurate map data.

Improving Driver Communication through One-Click Chat, Uber’s Smart Reply System

One-click chat, the Uber driver app's smart reply system, leverages machine learning to make in-app messaging between driver-partners and riders more seamless.
Food Discovery with Uber Eats: Recommending for the Marketplace

Food Discovery with Uber Eats: Recommending for the Marketplace

Uber Eats engineers describe how they surface restaurant recommendations in the app using multi-objective optimization to give eaters the most satisfying experience while maintaining the health of the Uber Eats marketplace.

Scaling Uber’s Customer Support Ticket Assistant (COTA) System with Deep Learning

Uber built the next generation of COTA by leveraging deep learning models, thereby scaling the system to provide more accurate customer support ticket predictions.

An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution

As powerful and widespread as convolutional neural networks are in deep learning, AI Labs’ latest research reveals both an underappreciated failing and a simple fix.
World map with stack of gold coins

Transforming Financial Forecasting with Data Science and Machine Learning at Uber

Uber developed its own financial planning software, relying on data science and machine learning, to deliver on-demand forecasting and optimize strategic and operations decisions.

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