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Rewiring Memory: A New Model That Learns Like a Human Brain
A new memory model called Input-Driven Plasticity (IDP) offers a more human-like explanation for how external stimuli help us retrieve memories, building on the foundations of the classic Hopfield network.
Credit: Neuroscience News“It’s a network effect,” said UC Santa Barbara mechanical engineering professor Francesco Bullo, explaining that associative memories aren’t stored in single brain cells. However, according to Bullo and collaborators Simone Betteti, Giacomo Baggio and Sandro Zampieri at the University of Padua in Italy, the traditional Hopfield network model is powerful, but it doesn’t tell the full story of how new information guides memory retrieval. While LLMs can return responses that can sound convincingly intelligent, drawing upon the patterns of the language they are fed, they still lack the underlying reasoning and experience of the physical real world that animals have.
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