By Martina Mihovska
AI seems to be everywhere now, from navigational tools to digital assistants and self-driven vehicles, the development in large part is a result of a particular technological convergence in recent years. The contaminant rise of big data, advanced methods of machine learning, and increasing computing power drives this perfect technological storm into a large-scale techno-social transformation across all sectors in society.
Innovative technologies, such as AI, have been considered key components in the contribution to the acceleration of numerous discoveries in life sciences, particularly in the field of Neuroscience. This article, therefore, discusses the fruitful relationship between AI and Neuroscience and its applications to furthering our knowledge in this field.
Artificial Intelligence is a term coined by emeritus Stanford Professor John McCarthy in 1955, defined by him as “the science and engineering of making intelligent machines”: much research has humans program machines to behave cleverly, consequently, neuroscience is the scientific study of the structure and cognitive function of the brain.
Alongside the advancements of AI systems, we may be able to drive neuroscience forward and unlock the secrets of the human brain with one of its applications being the ability to identify neurological problems and detect neurotransmitters.
The talented team of EyeMynd runs appropriate combinations of classical computers and quantum computers that spontaneously examine and understand the live-streaming optical brainwaves in real time to fine-tune themselves to the individual uniqueness of the personal living human brain.
Founder and CEO, Dan Cook, PhD in neuroscience at the University of California Berkley, describes the advanced nature of the human brain wave technology. He has developed complex computer algorithms for the detailed analysis of brainwaves, involving event-resolution imaging technology to interpret brain activity. EyeMynd is building a virtual reality system that you control with your brain intending to market a new type of VR headset – one that relies not on handheld controllers but on user brain activity.
While technology will get cheaper, Cook said that the EEG sensing technology will get more complicated allowing for more information to be interpreted. At first, this will be simple facial expression recognition, although later on, the expected outcome is the track of other body parts, emotion sensing, and more to become part of the interface.
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