Insane power efficiency, page-21

"how many existing products can be replaced with a neural network running on ultra low power".


Ummm...what do you think tinyML is all about?

TinyML takes edge AI one step further, making it possible to run deep learning models on microcontrollers, which are much more resource-constrained than the small computers that we carry in our pockets and on our wrists.

While a standard consumer CPUs consume between 65 watts and 85 watts and standard consumer GPU consumes anywhere between 200 watts to 500 watts, a typical microcontroller consumes power in the order of milliwatts or microwatts.

This low power consumption enables the TinyML devices to run unplugged on batteries for weeks, months, and in some cases, even years, while running ML applications on edge.

https://towardsdatascience.com/an-introduction-to-tinyml-4617f314aa79