Boffins unveil artificial intelligence that thinks just like we do - News Nation USA

Researchers at Fujitsu and the MIT Center for Brains, Minds and Machines (CBMM) have achieved a "major milestone" in the quest to bolster the accuracy of AI models tasked with image recognition. As described in a new paper presented at NeurIPS 2021, the collaborators have developed a method of computation that mirrors the human brain to enable AI that can recognize information that does not exist in its training data (also called out-of-distribution data, or ODD). Although AI is already used for image recognition in a range of contexts (e.g. the analysis of medical x-rays), the performance of current models is highly sensitive to the environment. The significance of AI capable of recognizing ODD is that accuracy is maintained in imperfect conditions – for example, when the perspective or light level differs from the images on which the model was trained. MIT and Fujitsu achieved this feat by dividing deep neural networks (DNNs) into modules, each of which is responsible for recognizing a different attribute, such as shape or color, which is similar to the way the human brain processes visual information.