More and more applications make up the machine learning on the device itself to offer a lower latency in predictions, a more efficient use of the battery and above all not to depend on a network connection, but this also entails some problems that now Google wants to solve.
Google has found that developers who implement machine learning in their applications run into application size limitations, performance differences, and limitations in the latest advances in machine learning. To solve these three problems Google will integrate TensorFlow Lite machine learning into Android.
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TensorFlow Lite for Android
Currently most of the applications that make use of machine learning integrate the library TensorFlow Lite in its APK by increasing the size of the application, with which Google has decided integrate TensorFlow Lite directly into Google Play Services.
TensorFlow Lite integration on all compatible mobiles prevents applications from having to integrate that library, thereby slightly reduces the size of applications, but it also brings two other important novelties.
This integration will also allow Google improve optimal performance on all the devices in your library. On some devices, machine learning may enable the hardware acceleration when available for some AI tasks to run in less time.
By integrating TensorFlow Lite API into Google Play Services you will receive regular updates on all versions of Android 4.4 or higher, thus covering practically all active devices on the market. In addition, Google is also working with chip vendors to update hardware drivers through Google Play, Qualcomm being the first partner.
The integration of TensorFlow Lite in the Google Play Services will come to Android by the end of the year. Starting today developers can point to preview to test the machine learning machine integration on Android.
Via | Android Developers
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The news
TensorFlow Lite machine learning integrates into Android to improve application size and performance
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