# Meta's Brain2Qwerty v2 Decodes Typed Sentences at 61% Word Accuracy

The non-invasive pipeline, based on magnetoencephalography (MEG), is a large improvement over earlier surgery-free methods, but it remains far from the below-2% error rate of surgical implants.

- Published: 2026-07-27T05:32:35.926Z
- Canonical: https://polylog.news/ai/2026-07-27/meta-s-brain2qwerty-v2-decodes-typed-sentences-at-61-word-ac
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [Meta AI](https://ai.meta.com/blog/brain2qwerty-brain-ai-human-communication/), [InfoQ](https://www.infoq.com/news/2026/07/meta-brain-interface/), [The Decoder](https://the-decoder.com/metas-non-invasive-brain-to-text-ai-is-closing-the-gap-with-surgical-implants/)

Meta's Brain2Qwerty v2 decodes typed sentences from non-invasive MEG signals at 61% word accuracy, with the best participant reaching 78% and more than half of sentences at one word error or fewer. The pipeline combines a convolutional enco…

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