Neural networks have learned to recognize 250 words uttered mentally

Scientists at the University of California have taken another step in teaching artificial intelligence to read human thoughts. Four women suffering from epilepsy took part in the experiment. All the subjects in different areas of the brain were implanted with electrodes, then the participants were asked to read aloud several sentences. The impulses from the brain regions were fed into the neural network, where the signals were processed. 

Volunteers read each sentence twice: the first time - to train the neural network, in the second time - to artificial intelligence to check whether the information was properly assimilated. Then the processed data were sent to the second neural network, where new sentences were prepared from the words received. In total, the neural network learned to recognize 250 words.  

At the same time, the probability of errors made by artificial intelligence when decoding impulses from the brain was only 3%. The authors of the research emphasize: this is the first work in which neural networks learned to recognize not individual words, but whole sentences. 

Based on this development, programs can be created that allow people who are unable to speak to communicate with others through thoughts. Despite the small vocabulary (250 words) that a person can use, he or she will be able to make sentences from them, which will significantly increase the opportunities for communication.

April 7, 2020, 10:11 a.m.

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