It has been revealed that there is a new mind-reading AI that translates thoughts without the person needing to have an implant. Check out the revolutionary discovery below.
Mind-reading AI
Australian researchers have developed a world-first AI system called DeWave that can convert silent thoughts into text.
The system requires users to wear a snug-fitting cap that records their brain waves via an electroencephalogram (EEG) and decodes them into text. In a recent test, more than two dozen participants read silently while wearing the cap.
With further refinement, DeWave could help stroke and paralysis patients communicate and make it easier for people to direct machines such as bionic arms or robots.
“This research represents a pioneering effort in translating raw EEG waves directly into language, marking a significant breakthrough in the field,” says computer scientist Chin-Teng Lin from the University of Technology Sydney (UTS).
In experiments conducted by Lin and his colleagues, DeWave achieved just over 40 percent accuracy based on one of two sets of metrics.
Although this is only a 3 percent improvement on the prior standard for thought translation from EEG recordings, it is a significant improvement.
The researchers aim to improve accuracy to around 90 percent, which is comparable to conventional methods of language translation or speech recognition software.
Other methods of translating brain signals into language require invasive surgeries to implant electrodes or bulky, expensive MRI machines, making them impractical for daily use. Moreover, these methods often need to use eye-tracking to convert brain signals into word-level chunks.
Science Alert notes the fact that after extensive training, DeWave’s encoder turns EEG waves into a code that can then be matched to specific words based on how close they are to entries in DeWave’s ‘codebook’.
“It is the first to incorporate discrete encoding techniques in the brain-to-text translation process, introducing an innovative approach to neural decoding,” explains Lin.
“The integration with large language models is also opening new frontiers in neuroscience and AI.”
