A team of AI researchers and computer scientists at the University of Alberta has found that current artificial networks used with deep-learning systems lose their ability to learn during extended training on new data. In their study, reported in the journal Nature, the group found a way to overcome these problems with plasticity in both supervised and reinforcement learning AI systems, allowing them to continue to learn.
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