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Gus Class (Gus)
3,252 followers -
It's ok, everything breaks eventually.
It's ok, everything breaks eventually.

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Head's up!
Making the G+1 button load more quickly

The G+1 button is shown billions of times per day on web pages around the world, so it’s important that it load as quickly and efficiently as possible. To make it easier for people to load and share the pages they’re interested in, we’ve created a simpler G+1 button sharing experience.

Beginning in a few weeks, clicking the +1 button will open a streamlined new Google+ sharing dialog, and the G+1 button will no longer display a +1 count. If you’re a publisher, you can rest assured that these +1s do not affect search ranking and the size and layout of the button will remain the same.

These changes will only affect the G+1 button outside of Google+. The +1 button within Google+ will continue to work the same way it always has.

If you’d like to view all of the pages you’ve +1’d over the years, you can download a list using Google Takeout.

We hope this change makes it that much easier to check out and recommend all the interesting things you discover!


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The Wall of Death in Seattle. In the way back times, skateboarders would half-pipe on the now parking cemented wall to the right of the photo. I have always found the piece to be very punk rock and sinister like the artist relished the potential for building something that would hurt someone. And yes, I have ridden skateboards and longboards along the north side of this public art.
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ICYMI - there's a new Google API for sign-in.

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Check out Firebase Authentication!

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Is it just me or is the Photos app still getting better at filtering random snaps into amazing pictures?
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Because GPU ain't cuttin' it for AI.
Tensor Processing Units (TPUs)
I'm very excited that we can finally discuss this in public. Today at Google I/O +Sundar Pichai revealed the TPU (Tensor Processing Unit), a custom ASIC that Google has designed and built specifically for machine learning applications. We've had TPUs deployed in Google datacenters for more than a year, and they are an order of magnitude faster and more power efficient per operation than other computational solutions for the kinds of models we are deploying to improve our products. This computational speed allows us to use larger, more powerful machine learned models, expressed and seemlessly deployed using TensorFlow (tensorflow.org) into our products, and to deliver the excellent results from those models in less time.

TPUs are used on every Google Search to power RankBrain (https://en.wikipedia.org/wiki/RankBrain), they were a key secret ingredient in the recent AlphaGo match against Lee Sedol, they are used for speech and image recognition, and they are powering a growing list of other smart products and features.

+Norm Jouppi and the rest of the team that developed this ASIC did a fabulous job, and it's great to see it discussed in public!

Blog post:
https://cloudplatform.googleblog.com/2016/05/Google-supercharges-machine-learning-tasks-with-custom-chip.html

Link to the part of the keynote where Sundar discusses TPUs:
https://www.youtube.com/watch?v=862r3XS2YB0&feature=youtu.be&t=7300

WSJ article:
http://www.wsj.com/articles/google-isnt-playing-games-with-new-chip-1463597820

Edit: Added a link and some text.

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#TIL I learned about the Stack Exchange 3D printer forum.

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Machine learn all the things! I'll take a deep dive into this in a future project.

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That new Start menu :)
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