Supercharging AI at the intelligent edge

As an Arm partner, we had early access to the new extensions and we can reveal that our already lean sound recognition software (ai3) will be at least 50% faster when running on chips based on the new Armv8.1-M architecture. As a result, we believe that the performance enhancements made possible by these new vector extensions will offer a major step change in tinyML.

Commenting on the launch, Dr Chris Mitchell, Audio Analytic’s CEO and Founder, said: “There is considerable demand to run advanced AI, like sound recognition, at the edge. Principally because cloud infrastructure is expensive and edge-based processing offers privacy benefits for end users. Now, thanks to Arm, consumer and IoT devices can deliver supercharged AI at even lower-power and lower-cost. The net result is being able to fit more features onto a device or being able to offer AI on an AA battery.”

Audio Analytic’s VP of Technology, Dominic Binks added: “With Helium, next generation Cortex-M processors gain the vectorising capabilities of NEON-class processors, along with other new capabilities, which together deliver tangible improvements in performance, and cost, in the microcontroller space.”