| Title: |
Artificial Intelligence at the Edge : A Joint European Roadmap for Edge AI |
| Authors: |
Lindgren, Anders; Azzoni, Paolo; Bierzynski, Kay; Daaldero, Gerardo; Dallemagne, Philippe; Diaznava, Mario; Duranton, Marc; Ecker, Wolfgang; Flak, Jacek; Hausrotter, Andreas; Katkoria, Deepak V; Langer, Jan; Magno, Michele; Mathis, Harald; Pau, Danilo; Peischl, Bernhard; Perlo, Pietro; Sawyer, Davis; Seifert, Inessa; Solanti, Petri; Taube, Markus; Tedesco, Salvatore; Vögel, Hans-Jörg; Weimer, Lars |
| Publisher Information: |
RISE Research Institutes of Sweden, Industriella system; INSIDE; Infineon Technologies AG; NXP Semiconductors; CSEM; STMicroelectronics; CEA-Leti; VTT Technical Research Centre of Finland Ltd; esc Aerospace GmbH; Logiicdev GmbH; Fraunhofer ENAS; ETH Zürich; Fraunhofer FIT; AVL List GmbH; I-FEVS Interactive Fully Electrical Vehicles S.r.l; VDI/VDE Innovation + Technik GmbH (EPoSS); Siemens AG; Research Studio; Tyndall National Institute; BMW Group; EPoSS e. V. |
| Publication Year: |
2025 |
| Collection: |
RISE (Sweden) |
| Subject Terms: |
Edge AI; artificial intelligence; embedded systems; neuromorphic computing; spintronics; hardware accelerators; IoT; machine learning; RISC-V; in-memory computing; European roadmap; EPoSS; Computer Sciences; Datavetenskap (datalogi) |
| Description: |
This white paper presents a joint European roadmap for Edge AI, developed by the EPoSS and INSIDE Edge AI Working Group. It provides an updated vision for artificial intelligence at the edge, covering the evolving cloud-edge-IoT infrastructure, AI and Edge AI development trends, new hardware architectures (including SNNs, RISC-V, photonics, chiplets, in-memory computing, ASICs, FPGAs), and key challenges and constraints driving innovation. The paper introduces MultiSpin.AI, a spintronics-based Edge AI coprocessor offering significant energy efficiency advantages. It further outlines KDT and Chips JU research and innovation timelines, analyses global market dynamics, and presents goals, objectives and recommendations for action to strengthen Europe's position in Edge AI. ; QC 20260401 |
| Document Type: |
report |
| File Description: |
application/pdf |
| Language: |
English |
| Availability: |
http://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-81280 |
| Rights: |
info:eu-repo/semantics/openAccess |
| Accession Number: |
edsbas.EE80B5AB |
| Database: |
BASE |