The future of Artificial Intelligence is increasingly moving beyond the cloud, towards distributed environments where data can be processed closer to where it is generated. At the same time, technologies such as Blockchain are opening new possibilities for decentralised, secure and trustworthy AI ecosystems. Exploring how these technologies can converge was at the heart of dAIEDGE’s special session at the 7th International Joint Conference on AI, Big Data and Blockchain in Granada, Spain.
As part of the conference, we organized the special session “Convergence of AI, Edge Computing and Blockchain”, held on 21 July and co-chaired by Jean-Marc Bonnefous and Oscar Deniz. The session, which served as Workshop D7.5 of WP7 and was organised by ETHZ/Tellurian, brought together researchers and business professionals to discuss emerging technologies, research developments and industrial perspectives at the intersection of AI, Edge Computing and Blockchain.
Also, we brought together different perspectives on how these technologies can interact to enable new approaches to decentralised AI, Edge infrastructures and distributed systems. The programme featured keynote presentations from external experts and leading professionals, including Marcello Mari, former founder and CEO of SingularityDAO, who opened the session with the keynote “Verifiable Intelligence: How Decentralized AI Evolved from Marketplaces to Governance Infrastructure”. His contribution explored the evolution of decentralised AI, from AI marketplaces towards new infrastructures focused on governance and verifiability.
Alongside these external perspectives, we also featured four research contributions selected by the organisers, addressing different challenges at the intersection of these technologies. These included MERCAI: A Decentralized AI Marketplace Prototype for Incentivized Edge Resource Sharing on Blockchain Infrastructure, focusing on decentralised Edge resource sharing through blockchain infrastructures, and An ODRL-Based Decentralized Framework for Licensing Distributed Heterogeneous Hardware Resources for Edge AI Benchmarking, proposing a framework for managing and licensing distributed and heterogeneous hardware resources for Edge AI benchmarking.
The programme also included contributions on the accelerated decoding of Centroid Positional Encoding for instance segmentation and anonymous participation in distributed AI systems, broadening the discussion towards efficiency and privacy within emerging distributed AI ecosystems.
We also welcomed Daniel Liebau from ESSEC Business School, who delivered the invited talk “On the Viability Bounds of Agentic Payments”. His contribution introduced an additional perspective on agentic systems and payment mechanisms, connecting technological developments with emerging models of interaction and transactions in decentralised digital environments.
The session concluded with a panel discussion on “Distributed AI: Convergence of AI, Edge Computing and Blockchain”, where we turned the discussion towards a key question for Europe: what industrial and investment priorities are needed for AI at the Edge to reach its full potential? The conversation highlighted that technological innovation needs to be accompanied by the right infrastructures, investment, collaboration and pathways to translate research results into real-world impact.
For us, the session was also an opportunity to strengthen one of the core objectives of dAIEDGE: connecting research, industry and the European ecosystem around the development of more distributed, efficient and trustworthy Edge AI. The convergence of AI, Edge Computing and Blockchain offers new opportunities for decentralised data processing and for building infrastructures capable of meeting the demands of next-generation intelligent systems.