Neuromorphic computing: Brain-Inspired AI and Hardware

These sources provide a comprehensive overview of **neuromorphic computing (NC)**, focusing heavily on specialized hardware and advanced Spiking Neural Network (SNN) architectures. One source, Open Neuromorphic, functions as a **hardware guide**, listing cutting-edge chips like Intel's Loihi, IBM's TrueNorth, and SynSense's Speck, detailing their specifications, release years, and capabilities like on-chip learning. The other sources explore the **rise and impact of NC**, emphasizing its energy efficiency—consuming up to 80% less power than conventional AI—and its crucial role in applications like edge AI, robotics, and solving complex optimization problems (Nheuristics). Furthermore, the articles discuss technical innovations like the **Spiking Token Mixer (STMixer)** architecture, designed to be compatible with event-driven asynchronous chips, and the challenges in mapping SNNs and encoding information using spike timing (temporal encoding) or frequency (rate encoding) for optimal hardware performance.Sources:• Neuromorphic Hardware Guide - Open Neuromorphic• 2025-08-07 The Rise of Neuromorphic Computing: How Brain-Inspired AI is Shaping the Future in 2025• 2023 Speck: A Smart event-based Vision Sensor with a low latency 327K Neuron Convolutional Neuronal Network Processing Pipeline https://arxiv.org/pdf/2304.06793• 2025-05-23 Neuromorphic-based metaheuristics: A new generation of low power, low latency and small footprint optimization algorithms https://arxiv.org/pdf/2505.16362

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