Innovating Works

EXTRA-BRAIN

Financiado
Explainable Trustworthy brain-like AI for Data Intensive Applications
In parallel to the current developments in the so-called narrow artificial intelligence (AI) realm, there is an urgent demand for more universal, general AI approaches that can operate across a wider spectrum of application domain... In parallel to the current developments in the so-called narrow artificial intelligence (AI) realm, there is an urgent demand for more universal, general AI approaches that can operate across a wider spectrum of application domains with varying data characteristics. It is expected that the emerging sustainable AI methods can be efficiently deployed in the edge-cloud continuum on different hardware platforms and computing infrastructure depending on the real-world task scenarios and constraints including the limited energy budget. In response to this growing demand and emerging trends we propose to adopt a brain-like approach to AI system design due to its promising potential for functional flexibility, hardware friendliness as well as energy efficiency among others. To this end, EXTRA-BRAIN is aimed at developing a new generation of AI solutions based on brain-like neural networks that enable us to overcome key limitations of the current state-of-the-art methods, exemplified by deep learning, such as limited cross-task generalisation and extrapolation to novel domains (bounded reliability), excessive dependence on costly annotated data as well as extensive training and validation processes with heavy demand for compute resources at high energy cost, to name a few. The core brain-like neural network design in our approach derives from the accumulated computational neuroscience insights into the brain's working principles of information processing, key learning schemes and neuroanatomical structures that underlie the brain's perceptual/cognitive phenomena and its functional flexibility. Furthermore, these novel models are supported by data optimisation pipelines, which improve data quality, security and reduce the costs of assembling suitable training data, and an explainability framework to empower the human user. The proposed EXTRA-BRAIN framework will be examined in a diverse set of use cases with different hardware demands in the edge-cloud continuum. ver más
28/02/2027
KTH
5M€
Duración del proyecto: 37 meses Fecha Inicio: 2024-01-01
Fecha Fin: 2027-02-28

Línea de financiación: concedida

El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-01-01
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
Presupuesto El presupuesto total del proyecto asciende a 5M€
Líder del proyecto
KUNGLIGA TEKNISKA HOEGSKOLAN No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico TRL 4-5