10⁴× more energy-efficient than CMOS. 2× the bandwidth.
A new class of intelligent hardware for low-power, high-performance AI
From synapse-inspired computing to scalable AI on chip:
SkyANN brings brain-like intelligence to the edge—fast, frugal, and secure
Skyrmions at Work: Neuromorphic Hardware for the Edge

From lab to device: how skyrmions, magneto-electric interfaces, and brain-inspired logic redefine neuromorphic computing

WHO WE ARE

At the frontier of Neuromorphic computing

SkyANN brings together a multidisciplinary consortium of leading European research institutions and industrial innovators. From skyrmionics and magneto-electric materials to semiconductor design and neuromorphic architectures, our partners span the entire stack of next-generation AI hardware. We operate across scientific, technological, and industrial domains to accelerate the transfer of breakthrough discoveries into scalable, low power electronics for real-world applications.

Reimagining Neural hardware

At SkyANN, we develop artificial neural networks built not from software, but from physical phenomena. Our approach uses skyrmionic quasiparticles to emulate the behavior of synapses and neurons at the nanoscale. By integrating these magneto-electric devices with CMOS electronics, we create neuromorphic chips that operate with 10,000× less energy and twice the bandwidth of traditional AI hardware. This is computing made for the edge—private, fast, scalable, and radically efficient.

neural research AI automation materials science

WHAT DO WE DO

Pioneering the future of low power AI chips

times lower target consumption

bandwith as target objective

What we do

At SkyANN, we develop artificial neural networks built not from software, but from physical phenomena. Our approach uses skyrmionic quasiparticles to emulate the behavior of synapses and neurons at the nanoscale. By integrating these magneto-electric devices with CMOS electronics, we aim to create neuromorphic chips that operate with 10,000× less energy and twice the bandwidth of traditional AI hardware. This is computing made for the edge—private, fast, scalable, and radically efficient.

How we do it

We design and prototype advanced semiconductor devices that enable ultra-efficient artificial intelligence. Through innovations in neuromorphic computing, skyrmionic data carriers, and energy-aware architecture, we are pushing the limits of what chips can do. SkyANN is not only building a working hardware prototype of a deep neural network—it’s laying the technological groundwork for Europe's next leap in AI hardware, aligned with the EU Green Deal and the Chips Act.

CONSORTIUM PARTNER

A European alliance for neuromorphic innovation

The SkyANN consortium is carefully balanced, its members span all the necessary technical competences and fields of research for this project and have access to infrastructure that exceeds standards. The project is built on leading expertise and strong prior collaborative links between partners. This long-standing collaboration has led to groundbreaking research and key publications that are foundational for SkyANN

Beratung für Data Science

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The Brain Engineering

Neural Engineering

Electrical Signals in the Brain

Systems Neuroscience

Machine Learning

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Neural Threads

Target Discovery

Neural Technology

Cognitive Neuroscience

Project timeline: milestones & deliverables

Charting a neuromorphic future: the roadmap of SkyANN

1st January 2024

Project Kick-Off

12th and 13th February 2024

Official Kick-Off Meeting in Manchester/UK

31st March 2024

SkyANN Visual Kit available \ Project Management Handbook delivered

30th June 2024

Risk Registry agreed \ Initial Data Management Plan ready

19th November 2024

SkyANN Advanced Dissemination, Communication and Exploitation Plan in place

27th February 2025

1-day Brain-Inspired Computing Workshop—Atoms to Bits: The Alphabet of Intelligence @ University of Manchester

5th March 2025

Fabrication of tailored MML samples

30th June 2025

Decision on the best promising MML systems for hosting skyrmions and one additional information carrier for prototype devices in WP2-3

30th June 2025

Validation of compact model of novel neuromorphic building block, the skyrmionic interconnect

1st August 2025

Design and simulations of demultiplexing devices

New age of skyrmion research

*Beratung für Data Science

our team

Our Scientists

Joel Yamaha, PHD

Board Director

Ingrid Vulk, PHD

Senior Executive

Jenna Olsen, MBA

Principal Scientist

Rachel Gray, PHD

DevOps Lead Engineer