It’s hard to believe that Glass started as little more than a scuba mask attached to a laptop. We kept on it, and when it started to come together, we began the Glass Explorer Program as a kind of “open beta” to hear what people had to say.
Explorers, we asked you to be pioneers, and you took what we started and went further than we ever could have dreamed: from the large hadron collider at CERN, to the hospital operating table; the grass of your backyard to the courts of Wimbledon; in fire stations, recording studios, kitchens, mountain tops and more.
Glass was in its infancy, and you took those very first steps and taught us how to walk. Well, we still have some work to do, but now we’re ready to put on our big kid shoes and learn how to run.
Since we first met, interest in wearables has exploded and today it’s one of the most exciting areas in technology. Glass at Work has been growing and we’re seeing incredible developments with Glass in the workplace. As we look to the road ahead, we realize that we’ve outgrown the lab and so we’re officially “graduating” from Google[x] to be our own team here at Google. We’re thrilled to be moving even more from concept to reality.
As part of this transition, we’re closing the Explorer Program so we can focus on what’s coming next. January 19 will be the last day to get the Glass Explorer Edition. In the meantime, we’re continuing to build for the future, and you’ll start to see future versions of Glass when they’re ready. (For now, no peeking.)
Thanks to all of you for believing in us and making all of this possible. Hang tight—it’s going to be an exciting ride.
Find out more about the types of charts available and get instructions for using the SPARKLINE function in the help center: http://goo.gl/2rWeIF.
Today's update to Calendar on the web brings a number of time-saving improvements:
Get event updates without refreshing
Google Calendar now displays changes to your calendar—such as new invitations or event updates—as soon as they happen. Now you don't need to refresh to make sure you see the latest changes.
See selected calendars without scrolling
For those of you who have more than a few calendars listed in “Other calendars”, you can now see at a glance which are currently displayed. The calendars you’ve selected to show will move to the top—so you don’t have to scroll through the whole list. Learn more: http://goo.gl/xJXtq9
Browser back button support
Tired of the ‘Back’ button in your browser not working? The Back button is now supported and will bring you to your previous view or date in Google Calendar.
Check out these new features the next time you're at calendar.google.com.
Neural networks have recently had great success in significantly advancing the state of the art on challenging image classification and object detection datasets. However, this accuracy comes at a high computational cost both at training and testing time.
But what if one takes inspiration from how people recognize objects, by selectively focusing on the important parts of an image instead of processing an entire image at once? By ignoring irrelevant noisy features in an image, fewer pixels need to be processed, substantially reducing classification and detection complexity.
Last week, during #NIPS2014 (goo.gl/uEHYAt), Google DeepMind presented Recurrent Models of Visual Attention, a paper which describes an “attention-based task-driven visual processing” that is capable of extracting information from an image or video by adaptively selecting a sequence of smaller regions (glimpses), processing only selected regions at high resolution.
Read the full paper at http://goo.gl/dEdWkk
This is a powerful pattern and one that you can use to accelerate your site as well. The key insight is that we are not speculatively prefetching resources and do not incur unnecessary downloads. Instead, we wait for the user to click the link and tell us exactly where they are headed, and once we know that, we tell the browser which other resources it should fetch in parallel - aka, reactive prefetch!
As you can infer, implementing the above strategy requires a lot of smarts both in the browser and within the search engine... First, we need to know the list of critical resources that may delay rendering of the destination page for every page on the web! No small feat, but the Search team has us covered - they're good like that. Next, we need a browser API that allows us to invoke the prefetch logic when the click occurs: the search page listens for the click event, and once invoked, dynamically inserts prefetch hints into the search results page. Finally, this is where Chrome comes in: as the search results page is unloaded, the browser begins fetching the hinted resources in parallel with the request for the destination page. The net result is that the critical resources are fetched much sooner, allowing the browser to render the destination page 100-150 milliseconds earlier.
P.S. Currently, reactive prefetch is only enabled for users of Google Chrome on Android, as it is the only browser that supports (a) dynamically inserted prefetch hints, and (b) reliably allows prefetch requests to persist across navigations. We hope to add support for other browsers once these features become available!
Suppose, hypothetically, that you wanted to count how many of your online friends were dogs, while preserving their privacy. One way to do this is to ask each online friend to flip a coin in secret. If the coin comes up heads, they tell you truthfully whether they are a dog or not, “Yes” or “No”. If tails, they answer “Yes”, regardless of their actual canine status.
A good estimate of the true count of your online canine companions then comes from the greater-than-half fraction of your friends that said they were dogs. However, you still wouldn’t know which of your friends was a dog: each answer “Yes” would most likely be due to that friend’s coin flip coming up tails.
Head over to the Google Research blog to learn about Randomized Aggregatable Privacy-Preserving Ordinal Response (RAPPOR), a new state-of-the-art, privacy-preserving open-source project that builds upon the above concept to learn software statistics that can be used to better safeguard users’ security, find bugs, and improve the overall user experience.
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