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EEAI 2026 to take place in Malta on 19-21 October

EEAI 2026, the European Conference on EDGE AI Technologies and Applications, will take place on 19-21 October in Mellieħa, Malta. EEAI brings together experts from academia and industry focusing on the edge artificial intelligence (AI) technology stack, edge AI frameworks, generative AI, agentic AI, architectures, algorithms, data types and methods, and applications.

EEAI 2026 will discuss the growing convergence of technologies affecting the edge AI ecosystem, including ubiquitous sensing in the internet of things (IoT), real-time processing in edge computing, generative AI (GenAI), and agentic AI. At the conference, participants will discuss topics such as:

  • integrating high-performance generative models directly onto devices for real-time, on-device content creation and reasoning;
  • bridging the gap between the digital and physical worlds with sensor-driven intelligence that perceives and interacts with its environment;
  • powering robots, drones and autonomous machines with onboard intelligence, enabling them to learn, adapt, and act without relying on the cloud; and
  • moving beyond simple inference to autonomous, goal-oriented agentic edge AI systems that can make complex decisions and execute tasks independently at the edge.

EEAI 2026 is co-organized by several leading European initiatives such as the large-scale Chips JU project EdgeAI and dAIEDGE network of excellence, in cooperation with other projects, including CLEVER, REBECCA, TRISTAN, NEUROKIT2E, LoLiPoP IoT, SMARTY and SMARTEDGE.

Participants at EEAI 2026 will have the opportunity to join the dAIEDGE Innovation Days, a co-located event on 21-22 October 2026 that showcases the latest cutting-edge developments in edge AI from a diverse range of innovative small and medium enterprises (SMEs).

EEAI 2026 banner

Summary

EEAI 2026 will occur in Mellieħa, Malta, from 19-21 October, focusing on edge AI technologies. Topics include real-time content creation, sensor-driven intelligence, and autonomous decision-making systems.