Thanks to pioneer DeepCube, the AI space has reached its next generation with the development of inference focused deep learning on edge devices.
DeepCube's innovation has enabled intelligent edge devices-e.g., mobile devices, security cameras, drones, agricultural machines… to make truly autonomous decisions by allowing software to run 10x faster while using less memory, freeing up smart devices former reliance from the cloud.
Such innovation has spawned many new possibilities including autonomous drones as well as a personalized healthcare management platform that serves as an AI companion to users.
In the former case, DeepCube has also enabled the deployment of autonomous drones who can operate without human intervention and Internet connectivity. Regular drones today have “software” brains that require cloud connectivity or are powered by Nvidia GPUs, which are expensive and relatively large in hardware footprint. In contrast, DeepCube’s technology enables the autonomous drone to have such a “brain” on device that has much faster response rates and that requires much less hardware processing power/footprint.
In the latter case of the healthcare management platform on DeepCube, we're referring to a system that would resides as an application on the user’s smartphone and/or wearable device (e.g. smart watch) which collects health data—such as blood glucose or oxygen levels, as well as vital signs- such as heart rate, blood pressure and body temperature and then provides real-time recommendations to users to help them improve their lifestyle and health, including predicting and preventing both small (e.g. cold or sleep deprivation) and dire health problems (e.g. diabetic shock or seizure).
This article is presented by T1.