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NimbleAI

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ULTRA ENERGY EFFICIENT AND SECURE NEUROMORPHIC SENSING AND PROCESSING AT THE END...

ULTRA ENERGY EFFICIENT AND SECURE NEUROMORPHIC SENSING AND PROCESSING AT THE ENDPOINT Today only very light AI processing tasks are executed in ubiquitous IoT endpoint devices, where sensor data are generated and access to energy is usually constrained. However, this approach is not scalable and results in high pen... ver más

30/09/2025

IKERLAN

9M€

Presupuesto del proyecto: 9M€

Líder del proyecto

IKERLAN S.COOP. No se ha especificado una descripción o un objeto social para esta compañía.

TRL 2-3 | 21M€

Fecha límite participación Sin fecha límite de participación.

Ver 21 Participantes

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-06-22

HORIZON-CL4-2021-DIGITAL-EMERGING-01-01: Ultra-low-power, secure processors... Expected Outcome:Proposals are expected to contribute to the following outcomes:

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

21 Participantes

IKERLAN

722.50K€ | Lider

BARCELONA SUPERCOMPUTING CEN...

566.25K€ | Participante

MONOZUKURI SOCIETA PER AZIO...

606.25K€ | Participante

CODASIP S R O

423.75K€ | Participante

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Duración del proyecto: 39 meses Fecha Inicio: 2022-06-22
Fecha Fin: 2025-09-30

Líder del proyecto

IKERLAN S.COOP. No se ha especificado una descripción o un objeto social para esta compañía.

TRL 2-3 | 21M€

Presupuesto del proyecto 9M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Today only very light AI processing tasks are executed in ubiquitous IoT endpoint devices, where sensor data are generated and access to energy is usually constrained. However, this approach is not scalable and results in high penalties in terms of security, privacy, cost, energy consumption, and latency as data need to travel from endpoint devices to remote processing systems such as data centres. Inefficiencies are especially evident in energy consumption. To keep up pace with the exponentially growing amount of data (e.g., video) and allow more advanced, accurate, safe and timely interactions with the surrounding environment, next-generation endpoint devices will need to run AI algorithms (e.g., computer vision) and other compute intense tasks with very low latency (i.e., units of ms or less) and energy envelops (i.e., tens of mW or less). NimbleAI will harness the latest advances in microelectronics and integrated circuit technology to create an integral neuromorphic sensing-processing solution to efficiently run accurate and diverse computer vision algorithms in resource- and area-constrained chips destined to endpoint devices. Biology will be a major source of inspiration in NimbleAI, especially with a focus to reproduce adaptivity and experience-induced plasticity that allow biological structures to continuously become more efficient in processing dynamic visual stimuli. NimbleAI is expected to allow significant improvements compared to state-of-the-art (e.g., commercially available neuromorphic chips), and at least 100x improvement in energy efficiency and 50x shorter latency compared to state-of-the-practice (e.g., CPU/GPU/NPU/TPUs processing frame-based video). NimbleAI will also take a holistic approach for ensuring safety and security at different architecture levels, including silicon level.

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