ReviewNature2025
Neuromorphic computing at scale.
Review in Nature, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
71 citing papers in PubMed.
- Metal Oxide Nano-Interface Boosting the Deep Ultraviolet Adjustable Noise-Filtering In-Sensor Computing.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Highly Stable and Non-Volatile Optoelectronic Synapses for Sensing, Memory, and Computing Enabled by a Deep-Potential Floating Gate.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Solution-Processed Multi-Junction Optoelectronic Synapses for Mode-Switchable SWIR Neuromorphic Vision Sensing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Implementation of offset corrected AGAD algorithm on 130-nm CMOS technology-based RRAM array for analog neural network training.Science advances · 2026Article
- Direct Triboelectric Programming of a Ferroelectric Synaptic Transistor for Neuromorphic Tactile Perception.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- A unified model of short- and long-term plasticity: Effects on network connectivity and information capacity.PLoS computational biology · 2026Article
- Emerging Multimodal Artificial Sensory Fusion Paradigms Toward Advanced Embodied Intelligence.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- A Reconfigurable Memristive Spiking Neuron Enabling Advanced Neuromorphic Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Temporal coding enables hyperacuity in event-based vision.Nature communications · 2026Article
- Neuromorphic Devices and Computing for Sensing, Memory, and Control.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Cerebellum-inspired neural network of supervised learning with tensor-based sparse coding for multi-class classification.PLoS computational biology · 2026Article
- Illuminating the Interface: In Situ Optical Insights Into Two-Electron ORR Pathways for HAdvanced materials (Deerfield Beach, Fla.) · 2026Review
- Hierarchical Multi-Mode Computing in Interlayer-Coupled 3D RRAM Crossbar Arrays.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Rapid and energy-efficient ultra-large library screening for drug discovery on a SpiNNaker2 neuromorphic chip.Communications chemistry · 2026Article
- Realization of the Bienenstock-Cooper-Munro rule in a single memristor.Nature communications · 2026Article
- Sustainable Synaptic Device with Two-Dimensional Ferroelectric Materials for Neuromorphic Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- 2D Materials Powering Neuromorphic Intelligence.Nano-micro letters · 2026Review
- Electronics with switchable flexibility for 3D conforming neural interfaces.Science advances · 2026Article
- Topological acoustic synapse for high-dimensional neuromorphic computing.Science advances · 2026Article
- Morphologically tunable mycelium chips for physical reservoir computing.Scientific reports · 2026Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neuromorphic computing is a brain-inspired approach to hardware and algorithm design that efficiently realizes artificial neural networks. Neuromorphic designers apply the principles of biointelligence discovered by neuroscientists to design efficient computational systems, often for applications with size, weight and power constraints. With this research field at a critical juncture, it is crucial to chart the course for the development of future large-scale neuromorphic systems. We describe approaches for creating scalable neuromorphic architectures and identify key features. We discuss potential applications that can benefit from scaling and the main challenges that need to be addressed. Furthermore, we examine a comprehensive ecosystem necessary to sustain growth and the new opportunities that lie ahead when scaling neuromorphic systems. Our work distils ideas from several computing sub-fields, providing guidance to researchers and practitioners of neuromorphic computing who aim to push the frontier forward.
Indexed as
Identifiers
39843589What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.