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Will humans eventually be able to power artificial intelligence with their own brain activity or thoughts?
Neurotechnology has advanced to the point where brain-computer interfaces (BCIs) can detect neural activity associated with specific thoughts, emotions, and actions, enabling people to control devices with their minds.
BCIs have been used to restore motor function in paralyzed individuals, allowing them to regain control over their limbs.
Researchers have developed a BCI that can decode and interpret brain signals associated with intended movements, enabling people to control robots and prosthetic limbs.
Brain-computer interfaces can also read brain signals associated with emotions, allowing for the development of emotion-sensing AI systems.
A 2020 study demonstrated the ability to decode and interpret brain signals associated with mental math problems, enabling people to solve math problems using only their brain activity.
BCIs have been used to develop brain-controlled exoskeletons, which can be controlled by people with paralysis or muscular dystrophy.
Researchers have developed AI-powered prosthetic limbs that can be controlled by the user's thoughts, using electroencephalography (EEG) to detect brain signals.
A 2019 study demonstrated the ability to use brain signals to control a robotic arm, allowing people to perform complex tasks using only their brain activity.
BCIs have been used to develop neurofeedback systems, which enable people to control their brain activity and emotions in real-time.
The first human-to-human brain interface was demonstrated in 2019, enabling people to control each other's actions using only brain signals.
Brain-computer interfaces can also be used to restore vision in visually impaired individuals, by directly stimulating the brain's visual cortex.
Researchers have developed AI-powered brain-computer interfaces that can detect and interpret brain signals associated with seizures, epilepsy, and other neurological disorders.
A 2020 study demonstrated the ability to use BCIs to detect and interpret brain signals associated with depression, enabling the development of AI-powered mood-sensing systems.
BCIs have been used to develop AI-powered brain-controlled wheelchairs, which can be controlled by people with severe paralysis or mobility impairments.
Researchers have developed AI-powered brain-computer interfaces that can detect and interpret brain signals associated with lie detection, enabling the development of AI-powered deception detection systems.
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