Get AI To Mobile Devices With Google TensorFlow Lite

Google has recently launched a TensorFlow Lite software for mobile devices supporting iOS and Android. TensorFlow Lite is specifically designed for machine learning developers to Kick Artificial intelligence up a notch. TensorFlow’s light weighted solution is now available as a developer preview. This software is ready to use for designing AI models that can run on iOS and Android apps. There are three AI based softwares in the trends these days. They are Google Assistant, Apple’s Siri, and Amazon’s Alexa. Anyone can get an AI based application unless they have Wifi connectivity and power source to plug in. 

TensorFlow lite enables on-device machine learning models with low latency inference and a small binary size. It also supports hardware acceleration with the Android Neural Networks API. A growing trend has been seen in consumer’s expectations. They want their devices to show human-like response. Previously launched TensorFlow is not the right fit for deploying AI in mobile devices. TensorFlow Lite is a basic move towards running AI models on mobile platforms and embedded devices. Now AI- powered devices will not only be accessible for the users but also disposable. It is aimed  to develop AI which has the ability to run algorithms on mobile devices without connecting to the cloud. TensorFlow lite will use its AI models in a highly optimised form on the CPU on majority of devices. 

The software focuses on these interests listed  below:

1. Developers don’t require internet connectivity and are capable of helping offline use cases.
2. Widely-available smart appliances create new possibilities for     on-device intelligence.
3. Interest in stronger user data privacy paradigms where user data does not need to leave the mobile device.
4. Innovation at the silicon layer is enabling new possibilities for hardware acceleration, and frameworks such as the Android Neural Networks API makes it easy to leverage these.

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Google asserted that the TensorFlow Lite is currently limited in functionality purposefully because the emphasis has been put on establishing a performance baseline over some of the most common AI models. It is leading the way for voice-controlled disposables. These are created on cheap chips and AI-powered appliances that don’t disclose your entire network to unethical hackers. 

Google’s  continuous  work  towards  putting more usefulness into less powerful devices is revolutionizing the computing world. Eventually, a world will be existing where AI system can be implemented cost-effectively into any gadget, even disposable ones. The span of Tensorflow lite will widen and and its potential will also grow and get advanced with time as the development carries forward.