SubsidieMeestersHybrid Spintronic Synapses for Neuromorphic Computing
Spin-Ion Technologies aims to develop neuromorphic chips using ion beam-engineered magnetic materials, bridging computational neuroscience and deep learning for efficient embedded systems.
Projectdetails
At Spin-Ion Technologies we develop a new manufacturing solution based on ion beam processes to precisely engineer magnetic materials at the atomic scale.
Introduction
This result enables the development of new neuromorphic chips based on low power synapses composed of magnetic devices that can overcome both catastrophic forgetting and reduce device variability. Hence, it greatly advances the development of highly efficient, robust hardware amenable to neural applications on the edge.
Project Overview
Our transition project involves both hardware and software developments to demonstrate the implementation of an Artificial Neural Network on a magnetic chip.
Objectives
This project will:
- Bridge computational neuroscience and deep learning.
- Generate a strong impact for future embedded and neuromorphic systems.
Commercial Readiness
This project also covers all necessary steps for full commercial readiness, including:
- Problem/solution validation
- Market research
- Competition analysis
- Establishing IP strategy
- Ensuring regulatory compliance
- Stakeholder engagements
- Dissemination activities
- Construction of a detailed business plan
- Securing future funding
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 2.499.998 |
| Totale projectbegroting | € 2.499.998 |
Tijdlijn
| Startdatum | 1-5-2023 |
| Einddatum | 31-10-2025 |
| Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- SPIN-ION TECHNOLOGIESpenvoerder
Land(en)
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Vergelijkbare projecten uit andere regelingen
| Project | Regeling | Bedrag | Jaar | Actie |
|---|---|---|---|---|
Coherent Spintronic Networks for Neuromorphic ComputingCOSPIN aims to develop and validate a novel all-spintronic neuromorphic computing network using spin waves for enhanced connectivity, reprogrammability, and efficiency in data processing tasks. | ERC STG | € 1.499.072 | 2022 | Details |
Memristive Neurons and Synapses for Neuromorphic Edge ComputingMEMRINESS aims to develop compact, power-efficient Spiking Neural Networks using memristive technology for enhanced collaborative learning on edge systems. | ERC STG | € 1.499.488 | 2022 | Details |
Solid-State Ionics Synaptic Transistors for Neuromorphic ComputingTRANSIONICS aims to develop stable, silicon-compatible solid-state synaptic transistors for neuromorphic computing, enhancing AI applications while ensuring scalability and integration with existing technology. | ERC POC | € 150.000 | 2022 | Details |
Metaplastic Spintronics SynapsesMETASPIN aims to develop low-power spintronic artificial synapses with metaplasticity to prevent catastrophic forgetting in AI, integrating this technology into an ANN for multitask learning applications. | EIC Pathfinder | € 2.999.750 | 2023 | Details |
Coherent Spintronic Networks for Neuromorphic Computing
COSPIN aims to develop and validate a novel all-spintronic neuromorphic computing network using spin waves for enhanced connectivity, reprogrammability, and efficiency in data processing tasks.
Memristive Neurons and Synapses for Neuromorphic Edge Computing
MEMRINESS aims to develop compact, power-efficient Spiking Neural Networks using memristive technology for enhanced collaborative learning on edge systems.
Solid-State Ionics Synaptic Transistors for Neuromorphic Computing
TRANSIONICS aims to develop stable, silicon-compatible solid-state synaptic transistors for neuromorphic computing, enhancing AI applications while ensuring scalability and integration with existing technology.
Metaplastic Spintronics Synapses
METASPIN aims to develop low-power spintronic artificial synapses with metaplasticity to prevent catastrophic forgetting in AI, integrating this technology into an ANN for multitask learning applications.