Brain2Qwerty
Meta's non-invasive brain-to-text research model that decodes typed sentences from MEG brain scans, aimed at communication for people with speech or motor disorders.
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Overview
Meta, with the Basque Center on Cognition, Brain and Language (BCBL), published Brain2Qwerty v2 on June 29-30, 2026 via the AI at Meta blog post "From Brain Waves to Words," alongside the original Brain2Qwerty v1 paper in Nature. The system uses end-to-end deep learning, fine-tuned on neural data to leverage semantic context, to decode typed sentences directly from raw magnetoencephalography (MEG) signals recorded non-invasively while volunteers type, without requiring brain surgery. Trained on roughly 22,000 sentences from nine participants (10 hours of MEG recording each), v2 reached 61% average word accuracy versus 8% for prior non-invasive approaches, with the top participant reaching 78% word accuracy and over half of decoded sentences containing one or fewer word errors; Meta released the v1/v2 training code and BCBL released the v1 dataset. This is a research system, not a shipped consumer or clinical product, aimed at eventually helping people with brain lesions or disorders that impair communication.
This is a sourced directory entry. Features and capabilities are reported in the linked sources; this entry does not document independent Aymorphic testing.
Key features
- Non-invasive decoding via magnetoencephalography (MEG), no brain surgery required
- End-to-end deep learning pipeline fine-tuned on neural data for semantic context
- 61% average word accuracy in v2 (vs. 8% for prior non-invasive methods); up to 78% for the best participant
- Trained on ~22,000 sentences across nine participants (10 hours of MEG recording each)
- Training code for v1 and v2 released by Meta; BCBL released the v1 dataset
Use cases
- Assistive communication research for people with speech- or motor-impairing conditions
- Academic and industry research into non-invasive brain-computer interfaces
Pricing
Not applicable — research project; training code released publicly, no commercial product or pricing.
Pricing reflects the source record and may change. Confirm current terms with the provider.
Dates and sources
- Released
- 29 Jun 2026
- Record updated
- 23 Sept 2026
- Record last checked
- 23 Sept 2026