Neuromorphic Computing

Brain-inspired computing that models biological neurons and synapses to achieve massive energy efficiency and real-time, event-driven processing.

Neuromorphic computing is a paradigm shift, moving past the Von Neumann architecture by integrating memory and processing to mimic the human brain's structure (Carver Mead, 1980s). The core technology is the Spiking Neural Network (SNN), where artificial neurons only 'fire' when a threshold is met (event-driven), drastically reducing power consumption; a human brain operates on about 20 watts, while training a large AI model can consume city-scale power. Hardware accelerators like Intel's Loihi 2 and the Human Brain Project's BrainScaleS and SpiNNaker systems implement this, enabling high-speed, low-latency applications (e.g., real-time sensory processing for autonomous vehicles and robotics).

https://open-neuromorphic.org