SubsidieMeestersMemristive self-organizing dendrite networks for brain-inspired computing
The MEMBRAIN project aims to develop self-organizing memristive nanonetworks for efficient, nature-inspired computing that mimics biological neural circuits, enhancing adaptability and intelligence.
Projectdetails
Introduction
Artificial Intelligence needs a hardware revolution to sustain the ever-growing demand for computing power in our society. The huge energy consumption and environmental impact of computation with current technologies is unsustainable.
Bioinspired Technologies
In the race toward future computing, bioinspired technologies have been shown as promising hardware solutions for computing beyond the Turing model and the classical von Neumann architectures.
New Device Concepts
Going beyond transistor-centered hardware solutions, the research community is exploring new device concepts and architectures that leverage physical phenomena for computing “in materia.” These concepts aim to emulate the effectiveness of information processing capabilities of our brain.
Memristive Devices
While arrays of memristive devices realized with a top-down approach represent emerging solutions for the hardware realization of artificial neural networks, these systems do not emulate the topology and emergent behavior of biological neuronal circuits.
Self-Assembly and Self-Organization
The principle of self-assembly and self-organization regulates both structure and functions, providing adaptability, efficiency, and robustness.
MEMBRAIN Project
Tackling the main challenges of neuromorphic computing, the MEMBRAIN project aims to develop a radically new concept of physically grounded computing nanoarchitecture based on self-organizing memristive nanonetworks of dendrites.
Information Processing
These networks are designed to efficiently process information and store knowledge on the same physical substrate at the matter level through physical laws.
Ambition and Goals
Overcoming the concept of nanotechnology as a simple advancement of microtechnology, the ambition is to compute like nature – thermodynamically – to push computation near the fundamental limits of efficiency.
Hardware-Software Codesign Framework
By establishing a hardware-software codesign framework at the crossroads of material science, machine learning, and neuroscience, the aim is to retarget the original goal of neuromorphic computing.
Conclusion
The goal is to create general-purpose truly intelligent systems that endow dynamic learning and multitasking capability.
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 1.487.500 |
| Totale projectbegroting | € 1.487.500 |
Tijdlijn
| Startdatum | 1-1-2025 |
| Einddatum | 31-12-2029 |
| Subsidiejaar | 2025 |
Partners & Locaties
Projectpartners
- ISTITUTO NAZIONALE DI RICERCA METROLOGICApenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
| Project | Regeling | Bedrag | Jaar | Actie |
|---|---|---|---|---|
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 Starting... | € 1.499.488 | 2022 | Details |
Heterogeneous integration of imprecise memory devices to enable learning from a very small volume of noisy dataThe DIVERSE project aims to develop energy-efficient cognitive computing inspired by insect nervous systems, utilizing low-endurance resistive memories for real-time decision-making in noisy environments. | ERC Consolid... | € 2.874.335 | 2022 | Details |
Neuromorphic Flexible Electro/chemical Interface for in-Memory Bio-Sensing and Computing.Develop a miniaturized, self-contained biosensing technology using neuromorphic devices for real-time monitoring and classification of neurodegenerative biomarkers in individualized healthcare. | ERC Starting... | € 1.500.000 | 2025 | Details |
Thermodynamic-inspired computing with oscillatory neural networksTHERMODON aims to revolutionize energy-efficient computing by integrating thermodynamics with neuromorphic architectures for self-organizing, adaptive AI systems. | ERC Consolid... | € 2.000.000 | 2024 | Details |
Perovskite Spiking Neurons for Intelligent NetworksThis project aims to develop compact perovskite-based devices that emulate neuron behavior for efficient spiking neural networks, enhancing perception and computation while reducing energy costs. | ERC Advanced... | € 2.498.004 | 2023 | Details |
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.
Heterogeneous integration of imprecise memory devices to enable learning from a very small volume of noisy data
The DIVERSE project aims to develop energy-efficient cognitive computing inspired by insect nervous systems, utilizing low-endurance resistive memories for real-time decision-making in noisy environments.
Neuromorphic Flexible Electro/chemical Interface for in-Memory Bio-Sensing and Computing.
Develop a miniaturized, self-contained biosensing technology using neuromorphic devices for real-time monitoring and classification of neurodegenerative biomarkers in individualized healthcare.
Thermodynamic-inspired computing with oscillatory neural networks
THERMODON aims to revolutionize energy-efficient computing by integrating thermodynamics with neuromorphic architectures for self-organizing, adaptive AI systems.
Perovskite Spiking Neurons for Intelligent Networks
This project aims to develop compact perovskite-based devices that emulate neuron behavior for efficient spiking neural networks, enhancing perception and computation while reducing energy costs.
Vergelijkbare projecten uit andere regelingen
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|---|---|---|---|---|
Hybrid electronic-photonic architectures for brain-inspired computingHYBRAIN aims to develop a brain-inspired hybrid architecture combining integrated photonics and unconventional electronics for ultrafast, energy-efficient edge AI inference. | EIC Pathfinder | € 1.672.528 | 2022 | Details |
SPIKING PHOTONIC-ELECTRONIC IC FOR QUICK AND EFFICIENT PROCESSINGSPIKEPro aims to develop an integrated neuromorphic chip combining electrical and photonic neurons to create efficient, high-speed spiking neural networks for diverse applications. | EIC Pathfinder | € 1.973.038 | 2024 | Details |
n-ary spintronics-based edge computing co-processor for artificial intelligenceMultiSpin.AI aims to revolutionize edge computing by developing a neuromorphic AI co-processor that enhances energy efficiency and processing speed, enabling transformative applications while reducing CO2 emissions. | EIC Pathfinder | € 3.143.276 | 2024 | Details |
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Hybrid electronic-photonic architectures for brain-inspired computing
HYBRAIN aims to develop a brain-inspired hybrid architecture combining integrated photonics and unconventional electronics for ultrafast, energy-efficient edge AI inference.
SPIKING PHOTONIC-ELECTRONIC IC FOR QUICK AND EFFICIENT PROCESSING
SPIKEPro aims to develop an integrated neuromorphic chip combining electrical and photonic neurons to create efficient, high-speed spiking neural networks for diverse applications.
n-ary spintronics-based edge computing co-processor for artificial intelligence
MultiSpin.AI aims to revolutionize edge computing by developing a neuromorphic AI co-processor that enhances energy efficiency and processing speed, enabling transformative applications while reducing CO2 emissions.
Distributed and federated cross-modality actuation through advanced nanomaterials and neuromorphic learning
CROSSBRAIN aims to revolutionize brain condition treatment using implantable microbots for real-time, adaptive neuromodulation and sensing in rodent models of Parkinson's Disease and Epilepsy.
Insect-Brain inspired Neuromorphic Nanophotonics
Developing nanophotonic chips inspired by insect brains for energy-efficient autonomous navigation and neuromorphic computing, integrating sensing and processing capabilities.