Scientists Develop A.I. System Focused On Turning Peoples’ Thoughts Into Text

According to a peer-reviewed study published on Monday in the journal Nature Neuroscience, scientists have developed an A.I. system focused on turning people’s thoughts into text.

Scientists have developed a noninvasive AI system focused on translating a person’s brain activity into a stream of text, according to a peer-reviewed study published Monday in the journal Nature Neuroscience.

The system, called a semantic decoder, could ultimately benefit patients who have lost their ability to physically communicate after suffering from a stroke, paralysis or other degenerative diseases. 

Researchers at the University of Texas at Austin developed the system in part by using a transformer model, which is similar to those that support Google’s chatbot Bard and OpenAI’s chatbot ChatGPT. 

The study’s participants trained the decoder by listening to several hours of podcasts within an fMRI scanner, which is a large piece of machinery that measures brain activity. The system requires no surgical implants.

Ph.D. Student Jerry Tang prepares to collect brain activity data in the biomedical imaging center at the University of Texas at Austin.

Once the AI system is trained, it can generate a stream of text when the participant is listening to or imagines telling a new story. The resultant text is not an exact transcript, rather the researchers designed it with the intent of capturing general thoughts or ideas. 

Alexander Huth, a neuroscientist at the University of Texas at Austin and co-author of a new study, has revealed that brain scans and artificial intelligence (AI) can be used to “decode” thoughts.

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