"The spray-on nature of the device allows it to conform to any size or shaped hand, but opens the possibility that the device could be adapted to the face to capture subtle emotional cues.

Machine learning then takes over. Computers monitor the changing patterns in conductivity and map those changes to specific physical tasks and gestures. Type an X on a keyboard, for instance, and the algorithm learns to recognize that task from the changing patterns in the electrical conductivity. Once the algorithm is suitably trained, the physical keyboard is no longer necessary. The same principles can be used to recognize sign language or even to recognize objects by tracing their exterior surfaces.

And, whereas existing technologies are computationally intensive and require vast amounts of data that must be laboriously labeled by humans—by hand, if you will—the Stanford team has developed a learning scheme that is far more computationally efficient.

Moreover, it's a surprisingly simple approach to this complex challenge that means we can achieve faster computational processing time with less data because our nanomesh captures subtle details in its signals," Kim added. The precision with which the device can map subtle motions of the fingers is one of the leading features of this innovation."

I imagine this innovation will help train robots to do specific tasks, which could increase our ability to automate.

Say you get Gordan Ramsay to cook a meal, you could spray this on his hands and track each individual movement of his cooking style. This could then be transferred to a robot which would have the ability to replicate those movements and decisions.

Any intricate task can be tracked, learned, and then automated with this technology.