Security News > 2020 > November > Researchers bring deep learning to IoT devices

MIT researchers have developed a system that could bring deep learning neural networks to new - and much smaller - places, like the tiny computer chips in wearable medical devices, household appliances, and the 250 billion other objects that constitute the IoT. The system, called MCUNet, designs compact neural networks that deliver unprecedented speed and accuracy for deep learning on IoT devices, despite limited memory and processing power.

IoT devices often run on microcontrollers - simple computer chips with no operating system, minimal processing power, and less than one thousandth of the memory of a typical smartphone.

With MCUNet, Han's group codesigned two components needed for "Tiny deep learning" - the operation of neural networks on microcontrollers.

The advance "Extends the frontier of deep neural network design even farther into the computational domain of small energy-efficient microcontrollers," says Kurt Keutzer, a computer scientist at the University of California at Berkeley, who was not involved in the work.

MCUNet could also bring deep learning to IoT devices in vehicles and rural areas with limited internet access.

News URL

http://feedproxy.google.com/~r/HelpNetSecurity/~3/-28UXDPuOhg/