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Announcing the winners of the #AndroidDevChallenge, powered by on-device machine learning

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Posted by Jacob Lehrbaum , Director of Developer Relations, Android Developers like you have always played an important role in Android innovation. Over 10 years ago, when we first launched the Android SDK, we also announced the Android Developer Challenge to reward model apps and highlight new ways of solving user problems. As Android pushes the boundaries of machine learning, 5G, foldables, and more, developers continue to help shape these new frontiers. To celebrate this work, we revived the challenge in 2019, with a focus on “Helpful Innovation,” powered by on-device machine learning. We received hundreds of creative projects, and at the end of last year, picked 10 winners who each combined a strong idea and a thirst to bring it to life. Since then, we’ve been working with those winners to help turn their ideas into reality. And today, we’re announcing the 10 winners . Some are still at the beginning of their journey but but their apps are now ready for you to download and try...

#AndroidDevChallenge: today is the last day to apply!

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Today is the last day to apply for the Android Developer Challenge ! And to spark your imagination, we wanted to take a look at one of the original Android Developer Challenge winners, from over 10 years ago. Meet Maurizio Leo : Maurizio and team have been working on Android for a while now. In fact, he was one of the winners of the original Android Developer Challenge, which launched with the start of Android over ten years ago. Their app , which won 3rd place worldwide at the time, has gone on to be downloaded over 30 million times! If you’ve got a great idea that can help users get things done, we want to hear! We’ll pick 10 concepts and provide expertise and guidance to those developers to help in their plans to bring their ideas to fruition, in part from this amazing set of experts we’ve assembled. And once the app is ready, we’ll help showcase it in front of the billions of users on Google Play, through a collection and more. You can read more about all of the prizes here . There...

Our panel of experts for the #AndroidDevChallenge (apply by Dec. 2)

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Just a little over a week left to finish your submission for the Android Developer Challenge, due December 2 ! Technology is enabling us to create a whole new era of helpful innovation by helping people get things done more quickly and surfacing patterns that would be difficult to detect using traditional methods. Ultimately, this helpful innovation is enabling us to live better, more productive, and safer lives. Earlier this week, we highlighted the type of helpful innovation ideas powered by machine learning which are the sort of examples we’re looking for, to help inspire you. Today, we wanted to share the names of the panel of experts we’ve assembled to help bring your projects to life as part of the Android Developer Challenge. These experts will be making the final decision on the 10 finalists of the Android Developer Challenge, and if you’re selected as one of those finalists, we plan to have you meet them when we bring you to Google HQ for a bootcamp next year: Dave Burke is ...

Android Developer Challenge: here’s what we’re looking for! (Apply by Dec. 2)

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Last month, we kicked off the next Android Developer Challenge , and asked you to submit your ideas focused on helpful innovation, powered by on-device machine learning. But what exactly do we mean when we say helpful innovation? We’re glad you asked! We rounded up a few of Google’s on-device machine learning offerings, together with some great recent examples of this technology in action, to help inspire your submission. Don’t forget, submit your idea by December 2! Using machine learning to tackle Fall Armyworm Take Nazirini Siraji. When she and a team of developers noticed a crop-pest threatening the livelihood of Ugandan farmers, they taught themselves TensorFlow to combat this pest. They collected training data from nearby fields in the form of images. With TensorFlow, they re-trained a MobileNet , a technique known as transfer learning and then used the TensorFlow Converter to generate a TensorFlow Lite FlatBuffer file which they deployed in an Android app. With the app, a f...

Android Developer Challenge: helpful innovation, powered by On-Device Machine Learning + you!

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Posted by The Android team Developers like you have always played an important role in shaping the direction of Android, fueling the wave of Android innovation. It’s the reason that when we first launched the SDK for Android 10+ years ago, we simultaneously announced the Android Developer Challenge: a way to help reward model apps and show us what user problems you wanted to solve. As Android continues to push the boundaries into emerging areas like ML, 5G, foldables and more, we need your help to bring to life the consumer experiences that will define these new frontiers. So we’re bringing back the Android Developer Challenge and asking you to help us unlock new experiences on Android, and help inspire other developers around these emerging technologies. As we kick off this challenge, the first area we’ll be focusing on is On-Device Machine Learning. At Google, we’re big believers in how this new technology can open up a world of helpful innovation so you can get things done in ways ...