Social media giant Meta recently released a breakthrough research result, which successfully developed a revolutionary brain-computer interface device that enables text input by reading neural signals from the human brain. The innovative technology was demonstrated in two detailed studies by a team of Meta scientists who used cutting-edge brain scanning technology and deep learning AI models to successfully decode the EEG signals generated by humans when typing, and even reconstruct the complete sentences . This breakthrough not only demonstrates the deep integration of technology and the human brain, but also opens up new possibilities for future human-computer interaction.
The core of this technology relies on a scanner called magneto-electroencephalography (MEG), which captures weak magnetic signals from the brain. Unlike traditional brain-computer interface technology, this device does not require invasive surgery and can work without direct contact with the brain, which greatly reduces the barriers to use and potential risks. However, the device also has significant limitations: it weighs nearly half a ton, costs up to $2 million, and can only be used in dedicated shielded rooms to avoid interference from Earth's magnetic field on the signal. In addition, the user must keep the head still during operation, and any slight movement may lead to signal loss.
Nevertheless, this technology has shown impressive potential. Research data shows that the system can detect keys pressed by a "skilled" typist with an accuracy rate of up to 80%. Although this accuracy has not yet reached perfection, it is enough to construct a complete sentence by decoding brain signals. To achieve this, the research team developed a deep learning system called "Brain2Qwerty" that learns and predicts the keys they press by observing thousands of characters entered by users.
Although the current technology is still a bit far from practical application, Meta researchers are confident in this discovery. They believe that this study not only verifies the theory that the human brain follows hierarchical structure in language formation, but also provides new ideas for the further development of artificial intelligence. Jean-Rémi King, head of Meta's Brain and AI team, said that a deep understanding of the workings of the human brain may bring breakthroughs to the development of machine intelligence.
Key points:
Meta has developed a non-invasive brain-computer interface device that can input text through brain signals.
The device weighs half a ton, costs up to $2 million, and needs to be used in special environments.
The current accuracy rate is 80%, but it still needs to be improved, and it is still a certain distance away from actual application.