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Research at Google
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Research at Google

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Exciting new research out of +Stanford University using #deeplearning and #TensorFlow to classify skin cancer. Read the paper at goo.gl/3KfHVW 
Artificial intelligence used to identify skin cancer | Stanford News
news.stanford.edu
In hopes of creating better access to medical care, Stanford researchers have trained an algorithm to diagnose skin cancer.
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Mark Anthony Richardson
 
Dr on star trac had one of those
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Understanding the various meanings of a particular word in text is key to understanding language, but for a computer, distinguishing between these meanings is so difficult that it has been described as “AI-complete”.

In order to help further progress on this challenge, we’re happy to announce the release of word-sense annotations on the popular MASC and SemCor datasets, manually annotated with senses from the NOAD. Learn more in the Research blog, linked below.
A Large Corpus for Supervised Word-Sense Disambiguation
research.googleblog.com
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In October 2015 we launched the Google Brain Residency (g.co/brainresidency), a 12-month program focused on jumpstarting a career for those interested in machine learning and deep learning research. And just seven months into the program, the Residents are already making an impact in the research field. See their publication on the Google Research Blog, linked below. To learn more and submit your application for the 2017 Google Brain Residency Program, visit g.co/brainresidency. Applications close January 13th, 2017.
Google Brain Residency Program - 7 months in and looking ahead
research.googleblog.com
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Iwuchukwu Obieze's profile photo
Iwuchukwu Obieze
 
Haaa ... humans! Always trying to steal it and run with it!!!
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Check out the second installment in the series on app discovery, where we discuss a deep learning framework to provide personalized recommendations to users.
App Discovery With Google Play, Part 2: Personalized Recommendations with Related Apps
research.googleblog.com
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To enable a more intuitive high-dimensional data exploration process, we are open-sourcing the Embedding Projector, a web application for interactive visualization and analysis of high-dimensional data recently shown as an A.I. Experiment, as part of TensorFlow.

We are also releasing a standalone version at projector.tensorflow.org, where users can visualize their high-dimensional data without the need to install and run TensorFlow. Learn more at the Google Research blog, linked below.
Open sourcing the Embedding Projector: a tool for visualizing high dimensional data
research.googleblog.com
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Martijn de Boer's profile photoMotiur Rahman's profile photoRasmus Fonseca's profile photo
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Rasmus Fonseca
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+Motiur Rahman .. the article says: "we are open-sourcing the Embedding Projector" and even gives a link that demonstrates how its set up to run offline.
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Three quadrillion pixels later, meet the new #EarthTimelapse , our most detailed view of Earth across space and time.
Our most detailed view of Earth across space and time
blog.google
Today, we're making our largest update to Timelapse yet, with four additional years of imagery, petabytes of new data, and a sharper view of the Earth from 1984 to 2016.
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Paul “Bear” Ravenstone
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These are amazing!
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We have recently published new guidelines to help data providers describe their datasets in a structured way, enabling Google and others to link this structured metadata with information to facilitate data discovery for others.
Facilitating the discovery of public datasets
research.googleblog.com
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The National Science Foundation (NSF) BIGDATA program "seeks novel approaches in computer science, statistics, computational science, and mathematics, along with innovative applications in domain science, including social and behavioral sciences, education, biology, the physical sciences, and engineering that lead towards the further development of the interdisciplinary field of data science."

We are happy to participate alongside other industry members to provide cloud credits/resources to qualifying NSF-funded projects, enabling researchers to obtain access to state-of-the-art cloud resources. Learn more about the program below.
Amazon Web Services, Google Cloud, and Microsoft Azure join NSF’s Big Data Program | NSF - National Science Foundation
nsf.gov
NSF's mission is to advance the progress of science, a mission accomplished by funding proposals for research and education made by scientists, engineers, and educators from across the country.
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Jon Van Oast's profile photoJose Gustavo Ramirez's profile photoRolf Müller's profile photo
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Rolf Müller
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WOW! Googlezonsoft.
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The Google Brain team's (g.co/brain) long-term goal is to create more intelligent software and systems that improve people's lives, which we pursue through both pure and applied research in a variety of different domains. And while this is obviously a long-term goal, we would like to take a step back and look at some of the progress our team has made over the past year.
The Google Brain team — Looking Back on 2016
research.googleblog.com
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K.W. Mc.
 
I won't hold you back
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Today, we are happy to announce a major new update to the #motionstills app (goo.gl/9mqSZX) that will help you create even more beautiful videos and fun GIFs using motion-tracked text overlays, super-resolution videos, and automatic cinemagraphs. Learn more on the Research blog, below.
Get moving with the new Motion Stills
research.googleblog.com
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Ondřej Vitík's profile photoRichard Vowles's profile photoAnders Feder's profile photoNicholas Peterson's profile photo
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Nicholas Peterson
 
+Jules Laplace yeah that seems weird
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NY Times Magazine reporter +Gideon Lewis-Kraus provides a great inside look at the Google Brain team (g.co/brain), its history, and what the team is working on.
The Great A.I. Awakening
How Google used artificial intelligence to transform Google Translate, one of its more popular services — and how machine learning is poised to reinvent computing itself.
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elton matimbe
 
Superb piece of journalism +The New York Times
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Learn more about our research being presented at the 30th Annual Conference on Neural Information Processing Systems ( #NIPS2016 ), in Barcelona this week. If you are attending, we hope you’ll stop by our booth and chat with our researchers about the projects and opportunities at Google that go into solving interesting problems for billions of people, and to see demonstrations of some of the exciting research we pursue.
Google at NIPS 2016
sites.google.com
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RICARDO MARTINEZ
 
Thanks for sharing +Research at Google 
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Introduction
Google is full of smart people working on some of the most difficult problems in computer science today. Most people know about the research activities that back our major products, such as search algorithms, systems infrastructure, machine learning, and programming languages. Those are just the tip of the iceberg; Google has a tremendous number of exciting challenges that only arise through the vast amount of data and sheer scale of systems we build.

What we discover affects the world both through better Google products and services, and through dissemination of our findings by the broader academic research community.  We value each kind of impact, and often the most successful projects achieve both.