Almost telepathy. A breakthrough technology has emerged for turning thoughts into text

December 27, 02:02 Share:

A computer has been taught to read human thoughts, turning them into text (Photo: prometeus / depositphotos)

Australian researchers have developed innovative DeWave technology. Their non-invasive AI system can turn silent thoughts into text using an ordinary cap with sensors.

Existing methods for translating brain signals into language require invasive surgery to implant electrodes in the brain or bulky, expensive MRI machines.. DeWave has made this process incredibly easy by recording participants' brainwaves using a cap with sensors to create an electroencephalogram ( EEG), they were subsequently decoded into text.

As Science Alert writes, while DeWave does not have very high accuracy – just over 40%, but the authors are confident that it is possible to achieve a result of 90%. To train the model, researchers from the University of Technology Sydney ( UTS) used language models ( BERT with GPT), which were tested on existing datasets created by tracking people's eye movements and brain activity while reading text. This data helped the system learn to match brainwave patterns with words from the DeWave “codebook.”

So far the system works best with verbs. There are a lot of difficulties with nouns. For example, the word The system understands “ author” as a more generalized “ person”.

“We think this is because when the brain processes these words, semantically similar words can create similar brain wave patterns,” says study first author Yiqun Duan, a computer scientist at UTS.

Despite this, scientist Chin-Ten Lin from UTS is confident that this system is a real breakthrough.

“This study is a pioneer in translating raw EEG waves directly into language, marking a significant breakthrough in the field.. … Despite the difficulties, our model produces significant results by aligning keywords and generating similar sentence structures. … Integration with large language models also opens up new frontiers in neuroscience and AI,” he notes.

The researchers hope to effectively improve the system and eventually make it useful for people with stroke and paralysis, and improve the ability to control bionic limbs and robots with it.

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