Project description
Adaptive, low-power AI at the edge
Edge AI systems such as those used in autonomous vehicles or medical diagnostics require fast, energy-efficient hardware to process data and adapt to challenging conditions in real time. However, traditional designs separate memory and processing, leading to high energy costs. The ERC-funded FELICE project plans to integrate memory and processing into a compact system by leveraging ferroelectric leaky integrate-and-fire neurons and FeFET-based non-volatile memory. This design will enable efficient temporal information processing and real-time learning without needing external training. Built on the 28 nm technology node, the design will help ensure scalability and commercial viability. Project activities will represent a major step forward in creating smarter, more efficient AI systems for edge applications.
Objective
The rapid growth of AI demands efficient hardware solutions that enable real-time learning and decision-making in power-constrained edge applications, such as autonomous systems, medical diagnostics, and industrial monitoring. However, current AI hardware faces fundamental trade-offs between power consumption, processing efficiency, and accuracy, limiting its deployment at the edge. Traditional computing architectures separate memory and processing, leading to high energy costs associated with data movement, while existing neuromorphic and analog AI solutions often lack efficient on-chip learning capabilities. FELICE introduces a breakthrough approach to edge AI hardware by co-designing a novel computing architecture that integrates processing and memory within a single compact system. By leveraging ferroelectric leaky integrate-and-fire (FeLIF) neurons and FeFET-based non-volatile memory (NVM), FELICE enables efficient temporal information processing and real-time learning at significantly lower power and area requirements compared to conventional designs. This eliminates the need for external training, allowing AI models to adapt dynamically to changing conditions, a key advantage for edge applications operating in unpredictable environments. A core innovation of FELICE is its training methodology, which optimizes learning at different time scales, overcoming key limitations in temporal AI processing. Furthermore, the 28 nm technological node enhances energy efficiency, making FELICE a scalable and commercially viable solution. By integrating hardware and software co-optimization, FELICE extends the capabilities of current CMOS technology to enable energy-efficient AI deployment at the edge, offering a transformative step towards compact, adaptive, and real-time AI solutions in high-impact domains.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been human-validated.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been human-validated.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering computer hardware
- natural sciences computer and information sciences artificial intelligence edge artificial intelligence
- engineering and technology nanotechnology nanoelectronics
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2025-POC
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
80333 Muenchen
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.