Researchers propose a new framework for lifelong learning in neural models, inspired by how animals learn and remember. They suggest that machine learning algorithms can benefit from asymmetric hemispheres with separate long- and short-term memory mechanisms, as well as periods of 'sleep' between learning tasks to consolidate memories. The authors present a novel architecture called 4MAS, which achieves competitive results on various benchmark datasets. --- Why it matters: This work matters because it aims to address the limitations of current machine learning approaches in lifelong learning, where models often forget previously learned information when adapting to new data. Understanding how animals learn and remembering can lead to more efficient and effective AI systems that can continuously learn from their environment without forgetting. Source: https://arxiv.org/abs/2608.19514