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Last updated : Oct 27, 2021
Oct 2021
Trial ? Worth pursuing. It is important to understand how to build up this capability. Enterprises should try this technology on a project that can handle the risk.

Since we first mentioned TensorFlow Lite in the Radar in 2018, we've used it in several products and are happy to report that it works as advertised. The standard use case is to integrate pretrained models into mobile apps, but TensorFlow Lite also supports on-device learning which opens further areas of application. Numerous examples on the website showcase many common areas of application, such as image classification and object detection, but also hint at new ways of interaction using, for example, pose estimation and gesture recognition.

May 2018
Assess ? Worth exploring with the goal of understanding how it will affect your enterprise.

TensorFlow Lite is the designated successor of TensorFlow Mobile, which we mentioned in our previous Radar. Like Mobile it is a lightweight solution tuned and optimized for mobile devices (Android and iOS). We expect the standard use case to be the deployment of pretrained models into mobile apps but TensorFlow Lite also supports on-device learning which opens further areas of application.

Published : May 15, 2018
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