Artificial neurons compute faster than the Human Brain
A computing system that mimics neural processing could make artificial intelligence more efficient — and more human.
By Sara Reardon on Nature
Superconducting computing chips modeled after neurons can process information faster and more efficiently than the human brain. That achievement, described in Science Advances on 26 January, is a key benchmark in the development of advanced computing devices designed to mimic biological systems. And it could open the door to more natural machine-learning software, although many hurdles remain before it could be used commercially.
Artificial intelligence software has increasingly begun to imitate the brain. Algorithms such as Google’s automatic image-classification and language-learning programs use networks of artificial neurons to perform complex tasks. But because conventional computer hardware was not designed to run brain-like algorithms, these machine-learning tasks require orders of magnitude more computing power than the human brain does.
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