# Meta发布Brain2Qwerty v2：非侵入式脑机接口实时解码自然句子

- 来源：Chubby♨️ (@kimmonismus)
- 发布时间：2026-06-30 05:49
- AIHOT 分数：56
- AIHOT 链接：https://aihot.virxact.com/items/cmqzs4ef400kbslkixpcdmp1j
- 原文链接：https://x.com/kimmonismus/status/2071712776226283902

## AI 摘要

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。

## 正文

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.

Meta is releasing the training code， while BCBL is releasing the v1 dataset， pushing brain-to-text research further into open neuroscience infrastructure.

I am so hyped for the future.

### 引用推文

> AI at Meta：We're sharing the next major milestone in our non-invasive brain-to-text decoder research: Brain2Qwerty v2. Building on v1, which was published today in @Nature...