Brain Inspired Computing

Brain-inspired computing aims to develop artificial intelligence systems that mimic the efficiency and capabilities of the human brain. Current research heavily focuses on spiking neural networks (SNNs), leveraging their energy efficiency and biological plausibility, often incorporating neuroscience insights into model design and training algorithms like those based on synaptic plasticity and knowledge distillation. This field is significant for its potential to create more powerful, energy-efficient AI systems and advance our understanding of biological neural computation, with applications ranging from improved human-computer interaction to more robust and adaptable computer vision.