普渡大学与佐治亚理工学院的研究团队在《科学前沿》发表研究，指出传统冯·诺依曼架构因内存与处理器分离导致“内存墙”问题，消耗大量时间和能源。为解决此瓶颈，他们提出利用类脑算法构建新型计算机架构，旨在显著降低人工智能模型的能耗。
["IBM研发NorthPole类脑芯片,可加速AI运算速度,比商用芯片快22倍。","NorthPole芯片内存与计算单元集成,大幅提升速度和能效。","NorthPole设计受人类大脑启发,采用核心内存减少冯诺依曼瓶颈影响。","NorthPole在图像识别测试中明显超过现有AI芯片,但内存有限。","NorthPole架构或可应用于自动驾驶等对速度敏感的AI应用中。"]
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