Dave Burke, VP of engineering at Google, announced a new version of Tensorflow optimised for mobile phones. This new library, called Tensorflow Lite, would enable developers to run their artificial intelligence applications in real time on the phones of users. According to Burke, the library is designed to be fast and small while still enabling state-of-the-art techniques. It will be released later this year as part of the open source Tensorflow project. At the moment, most artificial intelligence processing happens on servers of software as a service providers.
Consumers are beginning to expect more AI-driven interactions with their devices, whether they are interacting with smart assistants or expecting more tailored content within an application. However, when considering the landscape of available AI-focused applications, the list is significantly biased toward manufacturers. So, how can a third-party app developer provide an experience that is similar in performance and interactivity to built-in AI's like Siri or Google Assistant? This is why the release of TensorFlow Lite is so significant. TensorFlow released TensorFlow Lite, this past November as an evolution of TensorFlow Mobile.
When TensorFlow was first launched in 2015, we wanted it to be an "open source machine learning framework for everyone". To do that, we need to run on as many of the platforms that people are using as possible. We've long supported Linux, MacOS, Windows, iOS, and Android, but despite the heroic efforts of many contributors, running TensorFlow on a Raspberry Pi has involved a lot of work. Thanks to a collaboration with the Raspberry Pi Foundation, we're now happy to say that the latest 1.9 release of TensorFlow can be installed from pre-built binaries using Python's pip package system! If you're running Raspbian 9 (stretch), you can install it by running these two commands from a terminal: You can then run python3 in a terminal, and use TensorFlow just as you would on any other platform.