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This article discusses the advancements in neuromorphic computing and its impact on AI growth. It highlights the importance of new architectures and memory technologies, such as STT/SOTMRAM, SOT-MRAMs, ReRAMs, CB-RAMs, and PCMs, in driving this growth. The article also mentions the use of Spiking Neural Networks, Deep Neural Networks, and Restricted Boltzmann Machines in neuromorphic computing-based machine learning. Additionally, it discusses the nine major challenges faced by designers in this field.