Over the past decade, the CBICR team has defined and researched the challenges of developing neuromorphic computing without a complete understanding of the human brain. After nearly 10 years of dedicated effort, they successfully developed a comprehensive neuromorphic computing technology stack containing architecture, chips, systems, and software toolchains.Specifically, they proposed, for the...

In recent years, the computer science-oriented machine learning paradigm, mainly based on artificial neural networks, and the neuroscience-oriented neuromorphic computing paradigm, mainly based on spiking neural networks, have been widely studied and applied in intelligent systems. Each paradigm has its advantages and disadvantages in terms of applicable feature types, accuracy, robustness, and...