Recent Comments

    SNN tagged posts

    Brain-inspired AI architecture could computing faster and far less power-hungry

    June 24, 2026, Categories  Physics, Technology/Electronics

    New brain-inspired architecture could process data more efficiently
    Dual memory pathway abstraction. At the algorithmic level, each layer maintains a shared, low-dimensional state that captures slow contextual dynamics and modulates fast spiking activity. At the hardware level, this separation is mirrored by a heterogeneous accelerator that keeps the compact state on-chip and fuses sparse and dense computations for efficient execution. Credit: Sun et al.

    Spiking neural networks (SNNs) are artificial intelligence (AI) models inspired by how biological neurons communicate with each other. While biological neurons exchange information in the form of electrical impulses, SNNs rely on brief signals known as spikes.

    SNNs have proved promising for reducing power consumption, as developers can ensure they do not process information continuously, but rather ...

    Read More

    Brain-inspired Learning Algorithm realizes Metaplasticity in Artificial and Spiking Neural Networks

    September 5, 2023, Categories  Physics, Technology/Electronics

    Catastrophic forgetting, an innate issue with backpropagation learning algorithms, is a challenging problem in artificial and spiking neural network (ANN and SNN) research.

    The brain has somewhat solved this problem using multiscale plasticity. Under global regulation through specific pathways, neuromodulators are dispersed to target brain regions, where both synaptic and neuronal plasticity are modulated by neuromodulators locally. Specifically, neuromodulators modify the capacity and property of neuronal and synaptic plasticity. This modification is known as metaplasticity.

    Researchers led by Prof...

    Read More