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Meta AI's previous study (Brain2Qwerty) decoded typed text with a 32% character error rate (CER) by training a classifier time-locked to each key stroke. However, this approach faces three main challenges: 1. you need to know the timing of individual keystrokes, limiting real-time usage 2. keystroke classification does not guarantee effective sentence reconstruction 3. Very small dataset used to train the model
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