A group of scientists from the University of Texas has developed an artificial intelligence system that allows you to convert human brain activity into text. It is reported by RBC with reference to a study published in the journal Nature Neuroscience.
The scientists trained a semantic decoder on the mental activity of a subject who listened to several hours of podcasts while his brain was examined using an MRI machine. The designed system, which does not need to be implanted, can generate a stream of text when the user thinks. When the participants in the experiment watched the video without sound, artificial intelligence accurately described some of the events from the videos.
Scientists noted that the generated text is not an exact transcript, but only captures general thoughts or ideas. The system literally transmits the user’s words about half the time. For example, during the experiment, she imagined the thought “I don’t have a driver’s license yet” as “he has not even begun to learn to drive a car.”
The decoder relies in part on neural network models similar to those used by Open AI’s ChatGPT and the Google Bard chatbot, according to a press release from the University of Texas. “For a non-invasive method, this is a real leap forward compared to what has been done before. <…> We have obtained a model for decoding a continuous language over long periods of time with complex ideas,” said Alexander Hut, one of the lead authors of the study.
So far, the decoder cannot be used outside of laboratory conditions, since it only works with an MRI machine. But the researchers believe it could eventually be applied with more portable brain imaging systems. According to CNBC, the system will be able to help patients who have lost the ability to communicate after a stroke, paralysis or other degenerative diseases.
Source: Rosbalt
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