Data Needs: Predictive AI thrives on extensive labeled datasets for accurate forecasting, while generative AI can operate ...

Neuromorphic computing is an emerging computing technology inspired by the operational principles of the human brain. By employing neuromorphic devices to emulate neuronal functions and construct ...

The spiking neural network (SNN) computes and communicates information through ... color image dataset closer to universal objects and a benchmark test set of the CNN architecture. It contains 60,000 ...

A spiking neural network (SNN) is one of them ... the STDP plasticity was simpler and superior to other unsupervised learning rules in the same network architectures. The propagation of synaptic ...

EnCharge AI, a semiconductor startup developing analog memory chips for AI applications, has raised more than $100 million in ...

Abstract: Neuromorphic computing is concerned with designing computer architectures inspired by the brain, with recent work focusing on platforms to efficiently execute large spiking neural networks ...

Impact Statement: The SpikeNAS-Bench proposed in this paper heralds a leap in Neural Architecture Search (NAS) for Spiking Neural Networks (SNNs), offering a cell-based search space that magnifies ...

Efforts to build brain-inspired computer hardware have been underway for decades, but the field has yet to have its breakout ...

This study offers a valuable treatment of how the population of excitatory and inhibitory neurons integrates principles of energy efficiency in their coding strategies. The convincing analysis ...