Q3694267 (Q3694267): Difference between revisions
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(Created claim: summary (P836): This EMILE project aims to strengthen a collaboration between the Lens Mathematical Laboratory (LML) and Heart Never Lies (HNL). This collaboration is developing in response to the technological revolution induced by new advances in artificial intelligence. Indeed, the advent of deep neural networks is in the process of profoundly altering all fields of human activity. In particular, HNL quickly realised that this paradigm could challenge its t...) |
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This EMILE project aims to strengthen a collaboration between the Lens Mathematical Laboratory (LML) and Heart Never Lies (HNL). This collaboration is developing in response to the technological revolution induced by new advances in artificial intelligence. Indeed, the advent of deep neural networks is in the process of profoundly altering all fields of human activity. In particular, HNL quickly realised that this paradigm could challenge its technological advancement by offering not only alternatives to its patents but also new technical capabilities. That is why it has chosen to move ahead of these changes by seeking to build up skills in these new technologies. As a regional pioneer in deep learning, LML has been a privileged interlocutor for HNL. Future collaboration will focus on three main areas: 1. the search for innovative architectures and models, technological intelligence and technology transfer; 2. the generation of training data needed for the models to be developed; 3. adapting theoretical results to industrial problems. In addition, HNL will provide experimental data on which to test the models. (English) | |||||||||||||||
| Property / summary: This EMILE project aims to strengthen a collaboration between the Lens Mathematical Laboratory (LML) and Heart Never Lies (HNL). This collaboration is developing in response to the technological revolution induced by new advances in artificial intelligence. Indeed, the advent of deep neural networks is in the process of profoundly altering all fields of human activity. In particular, HNL quickly realised that this paradigm could challenge its technological advancement by offering not only alternatives to its patents but also new technical capabilities. That is why it has chosen to move ahead of these changes by seeking to build up skills in these new technologies. As a regional pioneer in deep learning, LML has been a privileged interlocutor for HNL. Future collaboration will focus on three main areas: 1. the search for innovative architectures and models, technological intelligence and technology transfer; 2. the generation of training data needed for the models to be developed; 3. adapting theoretical results to industrial problems. In addition, HNL will provide experimental data on which to test the models. (English) / rank | |||||||||||||||
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| Property / summary: This EMILE project aims to strengthen a collaboration between the Lens Mathematical Laboratory (LML) and Heart Never Lies (HNL). This collaboration is developing in response to the technological revolution induced by new advances in artificial intelligence. Indeed, the advent of deep neural networks is in the process of profoundly altering all fields of human activity. In particular, HNL quickly realised that this paradigm could challenge its technological advancement by offering not only alternatives to its patents but also new technical capabilities. That is why it has chosen to move ahead of these changes by seeking to build up skills in these new technologies. As a regional pioneer in deep learning, LML has been a privileged interlocutor for HNL. Future collaboration will focus on three main areas: 1. the search for innovative architectures and models, technological intelligence and technology transfer; 2. the generation of training data needed for the models to be developed; 3. adapting theoretical results to industrial problems. In addition, HNL will provide experimental data on which to test the models. (English) / qualifier | |||||||||||||||
point in time: 18 November 2021
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Revision as of 19:06, 18 November 2021
Project Q3694267 in France
| Language | Label | Description | Also known as |
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| English | No label defined |
Project Q3694267 in France |
Statements
180,068.0 Euro
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360,341.0 Euro
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49.97 percent
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1 January 2020
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31 December 2022
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Université d'Artois
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Ce projet EMILE a pour objectif de renforcer une collaboration entamée entre le laboratoire de mathématique de Lens (LML) et la société Heart Never Lies (HNL). Cette collaboration se développe en réponse à la révolution des techniques induite par les nouvelles avancées en intelligence artificielle. En effet, l’avènement des réseaux de neurones profonds est en train de modifier en profondeur l’ensemble des champs d’activité humaine. En particulier, HNL a très vite saisi que ce paradigme risque de remettre en cause son avancée technologique en offrant non seulement des alternatives à ses brevets mais aussi de nouvelles capacités techniques. C’est pourquoi elle a choisi de devancer ces changements en cherchant à monter en compétences dans ces nouvelles technologies. En tant que pionnier régional dans l’apprentissage profond, le LML a été un interlocuteur privilégié pour HNL. La collaboration à venir s'articulera autour de trois axes principaux : 1. la recherche d'architectures et de modèles innovants, veille technologique et transfert technologique ; 2. la génération de données d'entrainement nécessaires pour les modèles à développer ; 3. l'adapter des résultats théoriques aux problématiques industrielles. En outre HNL fournira des données expérimentales sur lesquelles tester les modèles. (French)
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This EMILE project aims to strengthen a collaboration between the Lens Mathematical Laboratory (LML) and Heart Never Lies (HNL). This collaboration is developing in response to the technological revolution induced by new advances in artificial intelligence. Indeed, the advent of deep neural networks is in the process of profoundly altering all fields of human activity. In particular, HNL quickly realised that this paradigm could challenge its technological advancement by offering not only alternatives to its patents but also new technical capabilities. That is why it has chosen to move ahead of these changes by seeking to build up skills in these new technologies. As a regional pioneer in deep learning, LML has been a privileged interlocutor for HNL. Future collaboration will focus on three main areas: 1. the search for innovative architectures and models, technological intelligence and technology transfer; 2. the generation of training data needed for the models to be developed; 3. adapting theoretical results to industrial problems. In addition, HNL will provide experimental data on which to test the models. (English)
18 November 2021
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Identifiers
NP0023856
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