Fusing deep learning and edge computing

IoT devices are explosively expanding, alleged to be tens of billions in the future. The key technologies are deep learning and edge computing.

It is not realistic to store and process all the data from IoT devices on cloud, as systems that require real-timeness largely exist. Deep learning fulfils its tremendous potential to analyze and perceive the enormous amount of data, while edge computing enhances the IoT system real-timeness.

And, to fuse those two concepts, easier to use, more flexible embedded deep learning framework is demanded. KAIBER is developed on this account.

KAIBER is easily-integratable into various edge devices, edge servers and applications on terminals, and significantly enhances the attractiveness of IoT solutions.