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Category: Mechanical Engineering

Machine intelligence at Dropbox: An update from our DBXi team

Our workdays are getting noisier. Never-ending emails, text messages, constant notifications from more apps and more platforms—it’s disruptive and distracting. And then there’s content. All kinds of documents, spreadsheets, presentations, videos, and photos. Industry research shows that employees at larger organizations use an average of 36 cloud services at work, including tools for productivity, project management, communication, and storage. This information overload is a key source of pain for people at work—and a prime opportunity to leverage the help of…

Google Glass – An Ultimate Creation

Google has launched its latest product named ‘Google Glass’ that opens a new path for the next generation to enter the world of technology. You might have heard of the wearable devices. Google Glass is a wearable computer which is in the form of sunglasses. It has a camera in it, that is helpful in capturing pictures and recording videos. It is easy for the users to use the product as a hands-free smartphone and allows the users to access…

Open Sourcing TonY: Native Support of TensorFlow on Hadoop

LinkedIn heavily relies on artificial intelligence to deliver content and create economic opportunities for its 575+ million members. Following recent rapid advances of deep learning technologies, our AI engineers have started adopting deep neural networks in LinkedIn’s relevance-driven products, including feeds and smart-replies. Many of these use cases are built on TensorFlow, a popular deep learning framework written by Google. In the beginning, our internal TensorFlow users ran the framework on small and unmanaged “bare metal” clusters. But we quickly…

Automated Fake Account Detection at LinkedIn

Although we prevent a large majority of bulk fake accounts from being created at registration, we sometimes don’t have enough information at that point to determine if accounts are fake. For this reason, we have other downstream models to catch smaller batches of fakes. First, we create clusters of accounts by grouping them based on shared attributes. We then find account clusters that show a statistically abnormal distribution of data, which is indicative of being created or controlled by a…

Expanding automatic machine translation to more languages – Facebook Code

Part of Facebook’s mission to bring the world closer together is breaking down language barriers and allowing everyone to engage with content in their preferred language. Translating more content in more languages also helps us better detect policy-violating content and expand access to the products and services offered on our platforms. When we factor in the number of languages in use and the volume of content on those platforms, we are serving nearly 6 billion translations per day to our…

Talking Safety with Uber Data Scientist Sunny Jeon

In the right hands, data can be a powerful tool, a key to understanding some of the most complex problems we face. Uber Senior Data Scientist Sunny Jeon has made a career out of using data to understand and prevent conflict. As applied at Uber, he studies the data around safety risks and builds models that help identify risk factors that could predict why and where conflicts or incidents might occur, so that we can develop policies and products designed…

Perfect patterns pave path to faster, cheaper MRI

Credit: University of Queensland A discovery by a University of Queensland researcher could speed up MRI scanning times and make the scans more affordable. Dr Shekhar Chandra from UQ’s School of Information Technology and Electrical Engineering has identified a new class of fractals, a mathematical pattern that could boost the MRI scanning process and allow a full body scan to be completed four times faster. “A variety of fractals have been discovered since the early 70s but none of…

Food Discovery with Uber Eats: Recommending for the Marketplace

Even as we improve Uber Eats to better understand eaters’ intentions when they use search, there are times when eaters just don’t know what they want to eat. In those situations, the Uber Eats app provides a personalized experience for each individual through restaurant recommendations. From search results to the list of restaurants and explicit recommendations on the app’s homescreen, we tailor the selection and ranking of restaurants to our understanding of what our  eaters crave. For example, an eater…

Forecasting at Uber: An Introduction

This article is the first in a series dedicated to explaining how Uber leverages forecasting to build better products and services. In recent years, machine learning, deep learning, and probabilistic programming have shown great promise in generating accurate forecasts. In addition to standard statistical algorithms, Uber builds forecasting solutions using these three techniques. Below, we discuss the critical components of forecasting we use, popular methodologies, backtesting, and prediction intervals.   Forecasting is ubiquitous. In addition to strategic forecasts, such as…

At last, a simple 3-D printer for metal

A sample part printed from bulk metallic glass via the TPF-based FFF process. Credit: Elsevier Used to produce three-dimensional objects of almost any type, across a range of industries, including healthcare, aviation and engineering, 3-D printed materials have come of age during the last decade. Research published in the journal Materials Today demonstrates a new approach to 3-D printing to fuse metallic filaments made from metallic glass into metallic objects. Jan Schroers, Professor of Mechanical Engineering and Materials Science at…