The brain communicates in short electrical clicks. Previously, to learn this language, thousands of examples with translations from the experimenter were needed. MOJO takes a different path: like learning a language through immersion, it first listens to the 'stream of consciousness' without any hints and finds recurring patterns on its own. Then, given a tiny dictionary, samples of signals linked to movements or words, it turns indistinct noise into clear commands.

Experiments on monkeys and mice showed that even one or two hints dramatically improve the results, outperforming classical algorithms hungry for data.

This cascade reduces uncertainty and allows working with any signals — from single neurons to large groups. It also clarifies the workings of living networks made of carbon. And since self-learning doesn't require expensive labels, vast accumulated archives of brain recordings can be put to use — bringing closer the era of assistive devices for people with paralysis. The idea is not new: as early as John von Neumann pondered the kinship of mind and machine.