Introducing TensorFlow Lite on the SparkFun Edge

#News(IoTStack) [ via IoTForIndiaGroup ]

The $14.99 SparkFun Edge is designed to run TensorFlow Lite models at the edge without a network connection. This enables developers to put the smarts on the smart device, rather than in the cloud.

Consuming around 0.3mA running flat out at 48MHz, and just 1 µA in deep sleep mode with Bluetooth turned off, the Apollo 3 processor’s power budget when running is less than many micro-controllers draw in deep sleep mode. That allows you to do real-time machine learning on a micro-controller board powered by a single CR2032 coin cell battery that should last for months.

The board can manage offline machine learning applications on the ‘Edge’ of networks, such as voice, gesture, or image recognition, with TensorFlow Lite at ultra-low power consumption, e.g. from a coin-cell battery.
There’s documentation specific to Sparkfun Edge development board, but you’ll also find a more generic getting started guide for Tensorflow Lite for microcontrollers in Github that also lists $2 Bluepill development board, STMicro STM32F746G Discovery Board, and Eta Compute ECM3531 EVB

“Ambiq Micro’s latest Apollo 3 Blue micro-controller whose ultra efficient ARM Cortex-M4F 48MHz (with 96MHz burst mode) processor can run TensorFlow Lite using only 6µA/MHz. Apollo3 Blue sports all the cutting edge features expected of modern micro-controllers including six configurable I2C/SPI masters, two UARTs, one I2C/SPI slave, a 15-channel 14-bit ADC, and a dedicated Bluetooth processor that supports BLE 5. On top of all that the Apollo3 Blue has 1MB of flash and 384KB of SRAM memory.”

https://www.youtube.com/watch?v=UGspuVY62BU&feature=youtu.be