# Meta's Brain2Qwerty v2 Decodes Typed Sentences From Brain Scans at 61% Accuracy

A non-invasive magnetoencephalography pipeline approaches the accuracy of surgical decoders, but remains too error-prone for daily use.

- Published: 2026-07-06T10:57:47.986Z
- Canonical: https://polylog.news/ai/2026-07-06/meta-s-brain2qwerty-v2-decodes-typed-sentences-from-brain-sc
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [Meta AI](https://ai.meta.com/blog/brain2qwerty-brain-ai-human-communication/), [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 published Brain2Qwerty, a non-invasive brain-to-text pipeline that decodes typed sentences from magnetoencephalography (MEG) recordings, a technique that measures the magnetic fields produced by brain activity. The version 2 system rea…

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