2026-07-25T03:03:22Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:19837 2026-04-20T13:04:17Z ddc:004 open_access

Edge-AI: Identifying Key Enablers in Edge Intelligence (Dagstuhl Seminar 23432) Ding, Aaron de Lara, Eyal Dustdar, Schahram Peltonen, Ella Meuser, Tobias cloud computing edge computing edge intelligence Edge computing promises to decentralize cloud applications while providing more bandwidth and reducing latency. Based on the discussion of our first Dagstuhl Seminar and the continuation work that took place after the seminar, we continued our work on identified challenges that need to be further addressed within the community. These challenges included 1) large-scale deployment of the edge-cloud continuum, 2) energy optimization and sustainability of such large-scale AI/ML learning and modelling, and 3) trustworthiness, security, and ethical questions related to the whole continuum. In this seminar, we discussed the current state of Edge Intelligence and shaped a holistic view of its challenges and applications. The main concerns were 1) the assessment and applicability of Edge Intelligence solutions, 2) energy consumption and sustainability, and 3) the new trend of Large-Language Models. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Aaron Ding and Eyal de Lara and Schahram Dustdar and Ella Peltonen and Tobias Meuser 2024 Is Part Of Dagstuhl Reports, Volume 13, Issue 10 (2024) Article Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagRep.13.10.130 urn:nbn:de:0030-drops-198376 https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.10.130 eng https://creativecommons.org/licenses/by/4.0/legalcode