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The brain is a remarkably capable and efficient system. It can process andstore huge amounts of noisy and unstructured information using minimal energy.In contrast, current artificial intelligence (AI) systems require vastresources for training while still struggling to compete in tasks that aretrivial for biological agents. Thus, brain-inspired engineering has emerged asa promising new avenue for designing sustainable, next-generation AI systems.Here, we describe how dendritic mechanisms of biological neurons have inspiredinnovative solutions for significant AI problems, including credit assignmentin multilayer networks, catastrophic forgetting, and high energy consumption.These findings provide exciting alternatives to existing architectures, showinghow dendritic research can pave the way for building more powerful andenergy-efficient artificial learning systems.

Leveraging dendritic properties to advance machine learning and neuro-inspired computing