According to a paper published by Nature Computational Science on Friday, the researchers developed a model that bridges the gap between big, externally complex AI networks and the small, internally complex workings of the brain.
Industry experts said the team’s findings could mark a pivotal shift in AI development, prompting further exploration of computing solutions that are not dependent on silicon chips.
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