Description du projet
Une nouvelle technologie pour une traduction automatique optimale
Une société innovante, inclusive et durable est une priorité européenne. Pour de nombreuses personnes, l’inclusion et la durabilité reposent sur une traduction vocale assurée par un dispositif intra-auriculaire léger basé sur l’internet des objets et tributaire de la connectivité internet. Cependant, bien que la traduction automatique se soit considérablement améliorée, l’utilisation de ces dispositifs est entravée par les réseaux neuronaux artificiels qui exigent des calculs intensifs, consomment énormément d’énergie et nécessitent des implémentations sur serveur. De plus, cela soulève des préoccupations croissantes en matière de protection des données et de la vie privée. Les transistors à effet de champ à nanofils verticaux ferroélectriques (VNWFET) offrent une solution. Grâce à la fabrication actuelle de VNWFET, le projet FVLLMONTI, financé par l’UE, va développer des couches matérielles empilées en 3D de réseaux neuronaux basés sur une co-optimisation matérielle et logicielle à grain fin permettant une traduction automatique des plus efficaces.
Objectif
"In the context of the fourth industrial revolution along with unprecedented growing global interdependencies, an innovative, inclusive and sustainable society is a sound European priority. For many people, the way towards inclusive and sustainable daily life goes through a lightweight in-ear device allowing speech-to-speech translation. Today, such IoT devices require internet connectivity which is proven to be energy inefficient. While machine translation has greatly improved, an embedded lightweight energy-efficient hardware remains elusive because existing solutions based on artificial neural networks (NNs) are computation-intensive and energy-hungry requiring server-based implementations, which also raises data protection and privacy concerns. Today, 2D electronic architectures suffer from ""unscalable"" interconnects, making it difficult for them to compete with biological neural systems in terms of real-time information-processing capabilities with comparable energy consumption. Recent advances in materials science, device technology and synaptic architectures have the potential to fill this gap with novel disruptive technologies that go beyond conventional CMOS technology. A promising solution comes from vertical nanowire field-effect transistors (VNWFETs) to unlock the full potential of truly 3D neuromorphic computing performance and density. Through actual VNWFETs fabrication setting up a design-technology co-optimization approach, the FVLLMONTI vision is to develop regular 3D stacked hardware layers of NNs empowering the most efficient machine translation thanks to a fine-grain hardware / software co-optimisation. FVLLMONTI consortium is a strong partnership with complementary expertise and extensive track-records in the fields of nanoelectronics, unconventional logic design, reliability, system‐level design, machine translation, cognition sciences. The consortium is composed of 50% of junior researchers and 90% of first-time participants to FETPROACT."
Champ scientifique
- natural sciencescomputer and information sciencesinternetinternet of things
- natural sciencescomputer and information sciencescomputer securitydata protection
- social sciencespolitical sciencespolitical transitionsrevolutions
- engineering and technologynanotechnologynanoelectronics
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Programme(s)
Régime de financement
RIA - Research and Innovation actionCoordinateur
33000 Bordeaux
France