Neural network accelerator chip enables IoT AI in battery-powered devices

The Maxim Integrated Products MAX78000 low-power neural network accelerated microcontroller moves AI to the edge without performance compromises in battery-powered IoT devices. Executing AI inferences at less than 1/100th the energy of software solutions dramatically enhances run-time for battery-powered AI applications while allowing complex new AI use cases once considered impossible. These power improvements come without compromise in latency or cost: the device executes inferences 100x faster than software solutions operating on low power microcontrollers, at a fraction of the cost of FPGA or GPU solutions.

By incorporating a dedicated neural network accelerator with a pair of microcontroller cores, the device enables machines to see and hear complex patterns with local, low-power AI processing that performs in real-time. Applications including machine vision, audio and facial recognition can be made more efficient since the device can execute inferences at less than 1/100th energy needed by a microcontroller. At the core of the device is specialised hardware intended to minimise the energy consumption and latency of convolutional neural networks. This hardware runs with the minimum of intervention from any microcontroller core, making operation particularly streamlined. Energy and time are only utilised for the mathematical operations that implement a CNN. To get data from the external world into the CNN engine efficiently, customers can employ one of the two integrated microcontroller cores: the ultra-low-power Arm Cortex-M4 core, or the even lower power RISC-V core.

“Artificial intelligence is frequently associated with big data cloud-based solutions,” said Kelson Astley, research analyst at Omdia. “Anything that can cut the power cord and reliance on big Lithium-Ion battery packs will help developers build AI solutions that are nimbler and more responsive to environmental conditions in which they operate.”

“We’ve cut the power cord for AI at the edge,” said Kris Ardis, executive director for the Micros, Security and Software Business Unit at Maxim Integrated. “Battery-powered IoT devices can now do much more than just simple keyword spotting. We’ve changed the game in the typical power, latency and cost tradeoff, and we’re excited to see a new universe of applications that this innovative technology enables.”