Scientists in Australia are working on a new artificial intelligence (AI) system that can turn brainwaves into text, meaning it can read a person’s thoughts without them speaking. This is being done by researchers at Sydney's University of Technology (UTS).

Usually, doctors use a tool called EEG (electroencephalogram) to check for brain problems. But now, these scientists are using EEG in a different way — to read what someone is thinking.

The AI system is being developed by PhD student Charles (Jinzhao) Zhou and his team members, Chin-Teng Lin and Dr Leong. They have created a deep learning AI model that can translate brain signals picked up from the EEG into actual words.

In one experiment, Dr Leong wore a special cap with 128 electrodes to record his brainwaves. He didn’t say anything out loud. Still, the AI model read his brain signals and showed the sentence:
"I am jumping happily; it's just me."

Right now, the AI system has been trained to understand only a small number of words and sentences. This helps the researchers test the system easily and improve how it recognises each word.

Dr Leong said that the AI is also helping to remove noise from the brain signals because brainwaves from different parts of the brain get mixed up when they reach the surface of the skull.

Unlike Elon Musk’s Neuralink, which involves surgery and is invasive, the Sydney team’s research is non-invasive. That means it does not need to be placed inside the brain.
"We can't get very precise because with non-invasive, you can't actually put it into that part of the brain that decodes words," explained Mr Lin.

This new technology could be very useful in the future for people who have had a stroke, children with autism, or those who are paralysed and can’t speak. It could help them communicate again.

Around the world, more scientists are also using EEG and AI together. For example, in April, researchers at Mass General Brigham built an AI tool that could predict brain decline years before it happens. The tool looked at brain activity during sleep and was able to correctly find 85% of people who later had memory problems, with 77% overall accuracy.

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