Neural networks are one of the disruptive computing concepts of our time. However, they
fundamentally differ from classical, algorithmic computing. These differences result in …

The proliferation of machine learning and neural networks in recent years has been spurred
on by the development of deep learning models and their usefulness in a wide variety of …

Photonic systems for high-performance information processing have attracted renewed
interest. Neuromorphic silicon photonics has the potential to integrate processing functions …

There has been a recent explosion of interest in spiking neural networks (SNNs), which
code information as spikes or events in time. Spike encoding is widely accepted as the …

Photonic brain-inspired platforms are emerging as novel analog computing devices,
enabling fast and energy-efficient operations for machine learning. These artificial neural …

Key to recent successes in the field of artificial intelligence (AI) has been the ability to train a
growing number of parameters which form fixed connectivity matrices between layers of …

Rapid advancements in deep learning over the past decade have fueled an insatiable
demand for efficient and scalable hardware. Photonics offers a promising solution by …

Progress in computing architectures is approaching a paradigm shift: traditional computing
based on digital complementary metal-oxide semiconductor technology is nearing physical …

Competitive photonic neural networks | Nature Photonics Skip to main content Thank you for
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In the emerging Internet of things cyber-physical system-embedded society, big data
analytics needs huge computing capability with better energy efficiency. Coming to the end …