TensorFlow can now run on $15 edge hardware

Experimental speech recognition demo on Cortex-M4 prototype board shows that the ‘intelligent edge’ is on the horizon

Google has introduced TensorFlow Lite 1.0, a framework for mobile and embedded devices, at its TensorFlow Dev Summit in California. TensorFlow Lite begins with training AI models on TensorFlow – Google’s computational framework for building ML models – which are then converted to create Lite models that can fit on mobile and embedded devices. It’s admittedly a far cry from the apps engineers hope one day be capable of running on edge devices, but when you look at the specifics it’s quite a feat: the model takes up only 20KB of flash storage space, the footprint of the TensorFlow Lite code just 25KB, and the app itself only 30KB of RAM.

Source: techerati.com