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Morning Edition · Saturday, July 18, 2026Published at 1:46 AM EDT · New York
Meta's Brain2Qwerty v2 Decodes Typed Sentences From Non-Invasive Brain Signals at 61% Word Accuracy
The pipeline, based on magnetoencephalography (MEG), cuts the average word error rate to 39% and reaches 22% for the best participant, but requires a room-scale scanner and per-subject training rather than real-time use.
Meta detailed Brain2Qwerty, a deep-learning system that reconstructs sentences from MEG recorded while participants type memorized sentences on a QWERTY keyboard. The latest version reaches an average word accuracy of 61%, with an average w…
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