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Michel Oleynik
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PhD Student at the Medical University of Graz, Austria
PhD Student at the Medical University of Graz, Austria

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TensorFlow Research Cloud: 1000 free Cloud TPUs for open machine learning research

Complementing our announcement of Cloud TPUs today, I'm also extremely excited that Google is offering 1,000 Cloud TPU devices, each capable of 180 TFLOPS of computation, for free to researchers doing open machine learning research. That's a total of 180 petaflops of computation (for comparison, the #1 supercomputer in the world now has an Rpeak of ~125 petaflops, per top500.org). As we've talked to machine learning researchers around the world, many of them tell us that they are computation limited: they believe that they could advance their research more quickly with access to more computation. TFRC is our way of helping the open machine learning research community move even more quickly and to tackle problems that are currently computation limited (as long as they are willing to openly publish their research and share feedback with the Cloud TPU team). See the blog post for details.

Nice work in getting TFRC to this point, +Zak Stone!

Relevant links:
TFRC blog post: https://research.googleblog.com/2017/05/introducing-tensorflow-research-cloud.html
Cloud TPU blog post: https://blog.google/topics/google-cloud/google-cloud-offer-tpus-machine-learning/
Cloud TPUs page: https://cloud.google.com/tpu/
Signup form to express interest in TFRC, Cloud TPUs, and TPU Pods: https://g.co/tpusignup

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We’re excited to announce the launch of Distill, a new open science journal and ecosystem supporting human understanding of #machinelearning. Distill is an independent organization, dedicated to fostering a new segment of the research community.

Led by a diverse steering committee of leaders from the machine learning and user interface communities, we are very excited to see where Distill will go. To learn more about Distill, visit the Google Research blog, below.
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