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The NEUROKIT2E project aims at proposing a Deep Learning Platform for Embedded Hardware around an established European value chain (providing AI hardware and software). This open source platform will provide the necessary tools for Europe to play on the same level with its American and Chinese competitors, and take the lead on a competitive aspect (still underdeveloped but which will quickly prove to be essential): embedded AI.
The NEUROKIT2E’s offer targets to serve European industry needs as a priority, enabling easy and fast Neural Network design, optimization and implementation on constrained hardware targets. This challenging development will be powered using N2D2 (for Neural Network Design & Deployment) platform, developed by CEA, Coordinator of NEUROKIT2E, for the exploration and development of AI applications, and embed specific hardware components from European players such as NX, ST, GML, all members of the NEUROKIT2E consortium. NEUROKIT2E will provide essential outcomes such as the end of the dependence of EU stakeholders to American and Chinese tools, the valorisation of EU hardware technologies, the benchmark of hardware and architectures before implementation to ensure the success of embedded AI in devices from energy consumption to sparse resources exploitation, the capacity to overcome the heterogeneity of components through a single, open, sovereign platform while ensuring reliability, safety, transparency. The NEUROKIT2E framework will impact the AI landscape as the first one dedicated to embedded AI and will position EU stakeholders in this key market. The NEUROKIT2E consortium relies on 5 EU countries active in the hardware and software activities, France, Netherlands, Austria, Germany and Italy, with a balance between private and public research: 12 private companies (5 large industries: THALES, Infineon, TTTECH, ST, DOLPHIN ; 6 SMEs: NX, GrAI, Almende, Spiki, Deep, HTS) ; 4 RTOs (CEA, IMEC, SAL, FBK).
This European Project, comprised of 25 partners, aims to provide an opensource and soverign platform of tools for Embedded AI with several ambitions:
1. Position EUROPE as a market leader by providing tools capable of meeting real-time, data confidentiality, energy consumption and usability requirements.
2. Provide a platform that will integrate hardware models with neural network models to optimize the network for embedded devices, and provide a single end-to-end development chain.
3. Develop advanced compression and pruning methods to reduce model size while maintaining the performance of the original network.
4. Enable the utilization of synchronous coding (tensors) and event-driven coding (spikes) to be combined into the same network.
This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101112268 . This publication [communication] reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.
On December 7, the NEUROKIT2E project held its second General Assembly in a virtual setting. This pivotal meeting showcased our first significant results and facilitated a comprehensive alignment on future plans, with a particular focus on refining our project management strategies.
The Kick-off Meeting (KoM) for the NEUROKIT2E project was successfully held on June 15 and 16 in Paris, marking the beginning of an exciting journey in advancing European embedded AI.