An AI revolution is brewing in medicine. What will it look like?
November 25, 2023Training Process
November 28, 20232017
Neuralink is a company founded to enable patients with paralysis, through small chips, to use smartphones with their minds faster than someone using their hands...
Neuralink is the first neural implant designated to help a computer or mobile device anywhere. It is based on micron-scale threads inserted into areas of the brain that control movement.(1,2,3)
Brain-Computer Interface
Brain-Computer Interface was founded in 2016 by Elon Musk, but it became publicly known in 2017. Neuralink is a medical research company currently developing two pieces of equipment. The first is a chip implanted into a person’s skull, and an array of tiny wires that fan out into the brain. These wires are not only able to monitor brain activity but also electrically stimulate the brain. The second one is a robot that can automatically implant the chip. It will work using a needle to punch the flexible wires emanating from a chip into the person’s brain.(1)
This neuroscience company aims to develop cranial computers that stimulate the right temporal sequences through electrodes by creating a method based on a direct cortical interface2. This will not only treat intractable brain diseases, such as Parkinson’s, epilepsy, and major depression but also help people with paralysis regain independence through controlling computers and mobile devices.2 It will also be easily accessible to avoid subjugation at the hands of intelligent machines.(3)
The technology currently faces several barriers, but Neuralink shows a promising pathway in which their technology will be able to increase the channels of communication with the brain. By this, they can access more significant areas of the brain and create new kinds of neural information.
This revolutionary company has the potential to study and treat a wide range of neurological disorders, restore both sensory and movement functions, and expand how we interact with each other. One of their biggest challenges is to design adaptive algorithms that maintain reliable and robust performance while, at the same time, continuing to improve over time, including adding new capabilities.(2)