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Noah Fiedel
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With fast compiler optimizations, API and documentation improvements, serve your models faster and easier than ever before!
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Learn how to go from research to production with TensorFlow Serving!

https://www.youtube.com/watch?v=sqYdlSF0BI8
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An inside look at the Google Brain team

For the past few months, we've had NY Times Magazine reporter +Gideon Lewis-Kraus visit the Google Brain team several times and hang out with us for a few days at a time, with an eye towards writing an article about how our research team operates and what we're working on. We gave him pretty open access to our building, the people in the team, many of our meetings, etc., and over the course of several visits, he decided to focus his story on the origins of the Brain team, and on our in-progress collaboration with the Google Translate team to replace the old phrase-based translation system with a neural machine translation system (essentially part of the article is a behind-the-scenes look at how the scientific work in https://arxiv.org/abs/1609.08144 and https://arxiv.org/abs/1611.04558 came about).

This long article is the result of his visits and synthesis of what he learned. Gideon, I think the article turned out really well!


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This is extraordinary. A must read if interested in image perception and automated captioning.
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Today, we're releasing two large datasets for robotics research:

Grasping: A collection of 650k grasp attempts, data used in: http://arxiv.org/abs/1603.02199

Push: A collection of 59k examples of pushing motions, data used in: http://arxiv.org/abs/1605.07157

Both datasets contain RGB-D views of the arm, gripper and objects, along with actuation and position parameters. They were collected in a controlled environment using a wide collection of everyday objects, some of which were held out for evaluation. Enjoy!

Credits: +Sergey Levine, +Chelsea Finn and +Laura Downs.
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Calistoga at dawn.
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6/5/16
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This is short and delightful ... and sad if you read through to learn more. Learn or not, enjoy this joyful bear :)

PS: about 33 seconds in the bear does something extra delightful.

https://www.youtube.com/watch?v=GN4svy6iGT4#t=33s
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TensorFlow 0.8 was released today, and had a number of nice improvements. It also takes the earlier changes for distributed models and packages them up so that they're easier to use. The blog post also has some scalability numbers for the distributed implementation for training a convolutional image recognition model.
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This is so good. A must watch for anyone interested in 10-X moonshots :)
Tackling gigantic shrinking challenges at X

Imagine if we could compress data to the point that we could speed compute times by 10X? Or if we could miniaturize physical objects, dramatically increasing global portability while reducing their carbon footprint? That’s what project compression is about.

We decided to bring in the best to work on this truly transformational technology. We've hired our first ever Chief Compression Officer, Richard Hendricks, to make our biggest moonshots, well, smaller.
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Congratulations to the Google Netherlands team for successfully moving self-driving technology from a car to a bike! We're excited to share learnings and see this self-driving bike technology in action on Dutch roads.
Google introduceert de zelfrijdende fiets in Nederland. We zijn trots dat een Nederlands team heeft gebouwd aan deze innovatie. #selfdrivingbike
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