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Sydney team develop AI model to identify thoughts from brainwaves

A team from the University of Technology Sydney has developed an AI model that can identify thoughts and translate them into text by analyzing brainwaves captured through an EEG cap. The model, which was trained on data from participants listening to podcasts, achieved an accuracy rate of 40% in translating thoughts into text, significantly higher than the previously reported 10% accuracy. This breakthrough could potentially assist individuals who are unable to communicate verbally, such as those with locked-in syndrome, by providing a new method for them to express their thoughts. The research, published in the Journal of Neural Engineering, marks a significant step forward in the field of brain-computer interfaces.

Read the Full rnz Article at:
[ https://www.rnz.co.nz/news/world/564253/sydney-team-develop-ai-model-to-identify-thoughts-from-brainwaves ]