Meta发布Brain2Qwerty v2,一种非侵入式脑机接口系统,能从实时脑信号解码完整自然句子,单词准确率达61%。系统基于约22000个句子训练,9名志愿者每人使用MEG记录10小时。相比此前非侵入方法8%的准确率大幅提升,最佳参与者达78%,超半数解码句子仅错一个词或更少。该端到端管线能实时将原始脑信号解码为单词和语义。但研究仍在受控实验室阶段:参与者样本小、依赖MEG硬件、数据来自主动打字、结果由公司报告,尚未成为临床通信设备。Meta已开源训练代码,BCBL发布v1数据集。
Meta says Brain2Qwerty v2 can decode natural sentences from non-invasive brain recordings in real time, reaching 61% word accuracy.
The system was trained on about 22,000 sentences from 9 volunteers, each recorded for 10 hours with MEG while typing.
Meta compares that with 8% word accuracy from prior non-invasive methods. Its best participant reached 78%, with more than half of sentences decoded with one word error or less.
This is still controlled lab research: small participant pool, MEG hardware, active typing data, and company-reported results. Not a clinical communication device yet.