# Meta's Brain2Qwerty Decodes Typed Sentences From Brain Scans at 61% Word Accuracy

The non-invasive system reads magnetoencephalography signals but still requires an immobile scanner in a shielded room and only works after a full sentence is typed.

- Published: 2026-07-21T05:32:28.125Z
- Canonical: https://polylog.news/ai/2026-07-21/meta-s-brain2qwerty-decodes-typed-sentences-from-brain-scans
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [Meta AI](https://ai.meta.com/blog/brain2qwerty-brain-ai-human-communication/), [Nature Neuroscience](https://www.nature.com/articles/s41593-026-02303-2), [MarkTechPost](https://www.marktechpost.com/2026/06/30/meta-ai-releases-brain2qwerty-v2-a-non-invasive-meg-brain-to-text-pipeline-decoding-typed-sentences-at-61-word-accuracy/)

Meta's Brain2Qwerty decodes typed sentences from non-invasive brain recordings, and its second version reaches an average 61% word accuracy from magnetoencephalography (MEG), up from roughly 8% for prior non-invasive approaches, MarkTechPos…

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