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neuromorphic computing

A collection of 15 posts

BiSpikCLM: Ushering in a New Era of Energy-Efficient AI Language Models

Spiking neural networks

BiSpikCLM: Ushering in a New Era of Energy-Efficient AI Language Models

Explore BiSpikCLM, a breakthrough in Spiking Neural Networks (SNNs) for large language models (LLMs). Discover how softmax-free attention and spike-aware distillation achieve significant energy savings for AI.

Advancing AI Reliability: New Generalization Bounds for Spiking Neural Networks

Spiking neural networks

Advancing AI Reliability: New Generalization Bounds for Spiking Neural Networks

Explore the latest theoretical advancements in Spiking Neural Networks (SNNs), offering precise generalization bounds for robust, real-world AI and IoT deployments.

Brain-Inspired AI: Enhancing Resilience of Neuromorphic Chips in Harsh Environments

neuromorphic computing

Brain-Inspired AI: Enhancing Resilience of Neuromorphic Chips in Harsh Environments

Explore how Spiking Neural Networks (SNNs) and on-chip learning enhance AI chip resilience against radiation, crucial for space and industrial deployments. Discover innovative radiation testing and the benefits of adaptive AI in extreme conditions.

EdgeSpike: Revolutionizing Edge IoT with Ultra-Low Power Spiking Neural Networks

Spiking neural networks

EdgeSpike: Revolutionizing Edge IoT with Ultra-Low Power Spiking Neural Networks

Discover EdgeSpike, a breakthrough SNN framework for IoT that delivers high accuracy with up to 47x energy reduction and 6.3x battery life extension for autonomous sensing at the edge.

Boosting Multimodal AI Efficiency: Inside SpikeMLLM's Breakthrough in Energy-Efficient Large Language Models

Boosting Multimodal AI Efficiency: Inside SpikeMLLM's Breakthrough in Energy-Efficient Large Language Models

Explore SpikeMLLM, a pioneering framework for energy-efficient Multimodal Large Language Models (MLLMs) using Spiking Neural Networks (SNNs). Discover how it tackles computational challenges with modality-specific temporal scales and temporal compression, enabling powerful AI on edge devices.

Enhancing Speech AI: How Bayesian Inference Smooths SNNs for Reliable Edge Deployment

Spiking neural networks

Enhancing Speech AI: How Bayesian Inference Smooths SNNs for Reliable Edge Deployment

Explore how Bayesian inference, using IVON, overcomes challenges in Spiking Neural Networks (SNNs) for speech processing, delivering smoother predictive landscapes and robust edge AI solutions.

Unlocking the Future of AI: How Open-Source Frameworks Are Bridging Physics and Machine Learning

Physical Reservoir Computing

Unlocking the Future of AI: How Open-Source Frameworks Are Bridging Physics and Machine Learning

Explore Physical Reservoir Computing (PRC) and OpenPRC, a unified open-source framework accelerating energy-efficient AI. Discover how it bridges physical systems with machine learning, enabling robust, physics-aware optimization for diverse applications.

Revolutionizing AI: Photonic Neural Networks Deliver Unprecedented Speed and Efficiency

photonic computing

Revolutionizing AI: Photonic Neural Networks Deliver Unprecedented Speed and Efficiency

Explore how photonic convolutional neural networks (PCNNs) overcome electronic computing limits with all-optical processing, offering unmatched energy efficiency and speed for enterprise AI applications.

Brain-Inspired AI for Edge Intelligence: Overcoming the Deployment Paradox

Spiking neural networks

Brain-Inspired AI for Edge Intelligence: Overcoming the Deployment Paradox

Explore how Spiking Neural Networks (SNNs) and hardware-software co-design are revolutionizing edge AI, addressing energy constraints, and driving a shift to efficient, brain-inspired computing.

Unlocking Compact AI: How Single Neurons with Autapses Reconstruct Complex Spiking Neural Networks

Spiking neural networks

Unlocking Compact AI: How Single Neurons with Autapses Reconstruct Complex Spiking Neural Networks

Explore how time-delayed autapses allow a single neuron to emulate complex Spiking Neural Networks, drastically reducing hardware footprint for efficient edge AI.

S2Act: Revolutionizing Edge AI with Efficient Spiking Neural Networks for Robotics

Spiking neural networks

S2Act: Revolutionizing Edge AI with Efficient Spiking Neural Networks for Robotics

Discover S2Act, a groundbreaking framework deploying energy-efficient Spiking Neural Networks for AI-powered robotics. Learn how it overcomes traditional SNN challenges for stable, real-world edge AI deployments.

AI dan Sirkuit Analog: Mengatasi Batasan Hardware untuk Kecerdasan Buatan yang Lebih Cepat

AI sirkuit analog

AI dan Sirkuit Analog: Mengatasi Batasan Hardware untuk Kecerdasan Buatan yang Lebih Cepat

Pelajari bagaimana pelatihan model *hardware-aware* memungkinkan *neural network* analog berbasis silikon mencapai akurasi ideal, membuka jalan bagi AI yang lebih efisien dan skalabel.

Unlocking Efficient AI at the Edge: How Neuromorphic Hardware is Transforming Industries

neuromorphic computing

Unlocking Efficient AI at the Edge: How Neuromorphic Hardware is Transforming Industries

Explore how neuromorphic computing and Spiking Neural Networks (SNNs) revolutionize edge AI, reducing power and latency for industrial applications. Learn about hardware optimizations and their business impact.

Personalized AI at the Edge: Revolutionizing Brain-Computer Interfaces with Neuromorphic Computing

Personalized AI

Personalized AI at the Edge: Revolutionizing Brain-Computer Interfaces with Neuromorphic Computing

Explore how personalized Spiking Neural Networks on ferroelectric hardware are enabling adaptive, low-power AI for EEG brain-computer interfaces, overcoming traditional challenges at the extreme edge for diverse industries.

Personalized Brain-Computer Interfaces: How Spiking Neural Networks & Ferroelectric Synapses Drive Ultra-Efficient Edge AI

Spiking neural networks

Personalized Brain-Computer Interfaces: How Spiking Neural Networks & Ferroelectric Synapses Drive Ultra-Efficient Edge AI

Explore how advanced Spiking Neural Networks on ferroelectric hardware are enabling personalized, low-power Brain-Computer Interfaces for real-time EEG processing, driving the future of adaptive Edge AI.