By now, it is very apparent that artificial intelligence or AI is not only changing the way people navigate through traffic, find new forms of entertainment, and shop online. AI has also drastically altered how many industries work, allowing scientists to come up with more realistic and innovative solutions to various global issues like finding alternatives to batteries and better understanding how our minds work, says Curtis Cripe of the neuroengineering research specialist NTL Group.
Image source: deepmind.com
AI is allowing for huge leaps in neuroscience, the strand of biology dealing with the anatomy and physiology of the human brain. Such a development is crucial in better understanding our behaviors, as neuroscience affects various fields spanning psychology and linguistics.
While deep learning is integral to modern AI studies, everything begins with the development of artificial neural networks or ANNs. An ANN is a computational model of the biological brain, something that neuroscientists were able to develop from breakthroughs in neurophysiology and psychology. Its goal is to detect patterns, allowing neuroscience to help validate current AI methods.
Image source: news.stanford.edu
It’s exciting that the relationship between neuroscience and AI is fast becoming a mutual one, as the former also benefits from the reinforced learning that AI provides, explains Curtis Cripe. While it must be noted that neuroscience’s provision of pattern detection does not necessarily equate to the correct approach in AI computation systems, neuroscience nonetheless ushers in myriad and complex arrays of algorithms and architectures that can be used to further AI innovations in the future.
Curtis Cripe, Ph.D., is the head of research and development at the NTL Group, which specializes in neuroengineering programs aimed at the diagnosis and treatment of neurological disorders connected to head injury, depression, anxiety, memory disorders, and learning disorders. More on Dr. Cripe and his work here.
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