The Google Brain team — Looking Back on 2016

Posted by Jeff Dean, Google Senior Fellow, on behalf of the entire Google Brain teamThe Google Brain team’s 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, and share what we feel may be in store for 2017.Research PublicationsOne important way in which we assess the quality of our research is through publications in top tier international machine learning venues like ICML, NIPS, and ICLR. Last year our team had a total of 27 accepted papers at these venues, covering a wide ranging set of topics including program synthesis,…
Original Post: The Google Brain team — Looking Back on 2016

Google Brain Residency Program – 7 months in and looking ahead

Posted by Jeff Dean, Google Senior Fellow and Leslie Phillips, Google Brain Residency Program Manager“Beyond being incredibly instructive, the Google Brain Residency program has been a truly affirming experience. Working alongside people who truly love what they do–and are eager to help you develop your own passion–has vastly increased my confidence in my interests, my ability to explore them, and my plans for the near future.”-Akosua Busia, B.S. Mathematical and Computational Science, Stanford University ‘162016 Google Brain ResidentIn October 2015 we launched the Google Brain Residency, a 12-month program focused on jumpstarting a career for those interested in machine learning and deep learning research. This program is an opportunity to get hands on experience using the state-of-the-art infrastructure available at Google, and offers the chance to work alongside top researchers within the Google Brain team.Our first group of residents arrived…
Original Post: Google Brain Residency Program – 7 months in and looking ahead

App Discovery With Google Play, Part 2: Personalized Recommendations with Related Apps

Posted by Ananth Balashankar & Levent Koc, Software Engineers, and Norberto Guimaraes, Product ManagerIn Part 1 of this series on app discovery, we discussed using machine learning to gain a deeper understanding of the topics associated with an app, in order to provide a better search and discovery experience on the Google Play Apps Store. In this post, we discuss a deep learning framework to provide personalized recommendations to users based on their previous app downloads and the context in which they are used.Providing useful and relevant app recommendations to visitors of the Google Play Apps Store is a key goal of our apps discovery team. An understanding of the topics associated with an app, however, is only one part of creating a system that best serves the user. In order to create a better overall experience, one must also…
Original Post: App Discovery With Google Play, Part 2: Personalized Recommendations with Related Apps

NIPS 2016 & Research at Google

Posted by Doug Eck, Research Scientist, Google Brain TeamThis week, Barcelona hosts the 30th Annual Conference on Neural Information Processing Systems (NIPS 2016), a machine learning and computational neuroscience conference that includes invited talks, demonstrations and oral and poster presentations of some of the latest in machine learning research. Google will have a strong presence at NIPS 2016, with over 280 Googlers attending in order to contribute to and learn from the broader academic research community by presenting technical talks and posters, in addition to hosting workshops and tutorials.Research at Google is at the forefront of innovation in Machine Intelligence, actively exploring virtually all aspects of machine learning including classical algorithms as well as cutting-edge techniques such as deep learning. Focusing on both theory as well as application, much of our work on language understanding, speech, translation, visual processing, ranking,…
Original Post: NIPS 2016 & Research at Google

Deep Learning for Detection of Diabetic Eye Disease

Posted by Lily Peng MD PhD, Product Manager and Varun Gulshan PhD, Research EngineerDiabetic retinopathy (DR) is the fastest growing cause of blindness, with nearly 415 million diabetic patients at risk worldwide. If caught early, the disease can be treated; if not, it can lead to irreversible blindness. Unfortunately, medical specialists capable of detecting the disease are not available in…
Original Post: Deep Learning for Detection of Diabetic Eye Disease

Enhance! RAISR Sharp Images with Machine Learning

Posted by Peyman Milanfar, Research ScientistEveryday the web is used to share and store millions of pictures, enabling one to explore the world, research new topics of interest, or even share a vacation with friends and family. However, many of these images are either limited by the resolution of the device used to take the picture, or purposely degraded in…
Original Post: Enhance! RAISR Sharp Images with Machine Learning