Clearly, there has been an increasing use of neural network based inference integrated with current artificial skin sensors in various applications ranging from robotics to health monitoring. However, due to a lack of on-skin compute, current skin sensors have to rely on off-body computers such as phones and cloud servers, for compute. This causes a significant slowdown in real time response.
We are working on developing AI-on-skin - a wearable artificial skin interface integrated with a neural network hardware accelerator that can be reconfigured across diverse neural network models and applications. AI-on-skin is designed to scale to the entire body, comprising tiny, low-power, accelerators distributed across the body. AI-on-skin is highly configurable, can run diverse neural networks, and support multiple applications.