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      <title>Meta's Noninvasive Brain–Computer Interface Brain2Qwerty Achieves 61% Accuracy</title>
      <link>https://www.infoq.com/news/2026/07/meta-brain-interface/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Deep+Learning-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/07/meta-brain-interface/en/headerimage/generatedHeaderImage-1783863685064.jpg"/&gt;&lt;p&gt;Meta recently open-sourced Brain2Qwerty v2, a noninvasive Brain–Computer Interface (BCI) that can decode sentences from thoughts using electroencephalography (EEG) or magnetoencephalography (MEG) signals from the brain. In evaluations, the system achieved a word accuracy rate 61% on average, compared to 8% for other non-invasive methods.&lt;/p&gt; &lt;i&gt;By Anthony Alford&lt;/i&gt;</description>
      <category>Deep Learning</category>
      <category>Neural Networks</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Tue, 14 Jul 2026 13:00:00 GMT</pubDate>
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      <dc:creator>Anthony Alford</dc:creator>
      <dc:date>2026-07-14T13:00:00Z</dc:date>
      <dc:identifier>/news/2026/07/meta-brain-interface/en</dc:identifier>
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