# Meta's Brain2Qwerty v2 Decodes Typed Sentences From Non-Invasive Brain Signals at 61 Percent Word Accuracy

The pipeline reads magnetoencephalography while a person types and reconstructs the text in real time, but it still requires a 306-sensor scanner in a shielded room and has only been tested on healthy participants during actual typing.

- Published: 2026-07-15T05:45:50.502Z
- Canonical: https://polylog.news/ai/2026-07-15/meta-s-brain2qwerty-v2-decodes-typed-sentences-from-non-inva
- 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 sentences that a person types by reading brain activity without any implant or surgery, and the v2 system reconstructs the text in real time. Meta reports average word accuracy of 61 percent for the v2 pipeline r…

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