A foundation model for neural decoding that translates EEG signals into identifiable objects, texts, and images
A foundation model for neural decoding that translates EEG signals into identifiable objects, texts, and images.
Current methods of direct brain-to-device communication require invasive surgery and are fraught with technical limitations, making it difficult to accurately decode inner speech.
The solution involves using EEG to non-invasively record brain activity and decode the neural processes involved in reading, listening, and generating inner speech into communicable language.
1 founders including Co-founder