From Brain Waves to Words: Brain2Qwerty Offers a New Path to Communication Without Surgery

Meta AI Blog

Brain2Qwerty v2 decodes sentences from non-invasive brain recordings using AI trained on neural signals, without requiring surgical implants. The system achieved 61% word accuracy across nine participants wearing MEG devices while typing, with the best participant reaching 78% accuracy. The researchers released full training code and datasets to enable broader development of non-invasive brain-computer interfaces for people with communication disorders.

Why it matters

Last year, we introduced Brain2Qwerty v1, research that uses AI to decode brain activity into text without any surgical implant. Now we're sharing the next step: Brain2Qwerty v2, the highest-performing end-to-end pipeline capable of real-time sentence decoding from non-invasive brain recordings, approaching levels of accuracy previously exclusive to techniques that require brain surgery.