The use of artificial intelligence (AI) in Edge computing is entering a new era based on the use of ubiquitous small and connected devices. Until now, Europe has not been doing well, as America sets the standards and most components are produced in Asia or America. This project believes doing better is realized by (1) Putting European values of self-organization, privacy by design and low use of energy in the core of the Edge Computing components that shape this new era, and delivering the technology needed to promote these values; (2) Focusing on pan European cooperation to ramp up the capabilities needed to deliver these new components at a scale that can make a real impact. Europe does not have huge IT leaders so cooperation from a very early phase is key. All partners in the project participate in delivering key parts of these new Edge Computing components; and (3) Demonstrating the use of these components in key European industrial areas. Clear and early examples are needed to un-lock corporate and external funding to deliver on the promise of this very exciting project. The DAIS project will research and deliver distributed artificial intelligent systems. It will not research new algorithms, as such, but solves the problems of running existing algorithms on these vastly distributed edge devices that are designed based on the above three European core values. The research and innovation activities are organized around eight complementary and mutually supportive supply chains. Five of these focus on delivering the hardware and software that is needed to run industrial-grade AI on different types of networking topologies. Three of the supply chains demonstrate how known AI challenges, from different functional areas, are met by this pan European effort. The DAIS project consists of 48 parties from 11 different countries. The DAIS project fosters cooperation between large and leading industrial players from different domains.

Data-driven innovation will bring enormous benefits for citizens, affecting all sectors of activity and the daily lives of all Europeans. It will enable, for example, AI-driven services to find causes for diseases or share attributes of individuals’ identity to quickly participate, for instance, in social or education activities across Europe. However, identity compromises, leakages or abuses of this kind of data pose serious threats that may compromise the proliferation of data spaces involving personal data, and reduce the opportunities offered by the data economy. The goal of the TrustED project is to design and develop a robust self-sovereign identity management method with advanced features as well as a set of combined privacy enhancing technologies (PETs) to enable TWO highly scalable and reliable services on personal data within data spaces with privacy guarantees that exceed the requirements of the GDPR, eIDASv2 and EUDI wallet: (1) A trustworthy federated learning service combined with several PETs that will allow AI-powered studies of siloed datasets with privacy guarantees. (2) A scalable and reliable self sovereign identity management service combined with methods for AI-based document validation, multimodal biometrics and ZKP-based selective disclosure techniques, that will enable electronic attestation, revocation of credentials and sharing of specific attributes of identity in a privacy preserving way. The components will be piloted, demonstrated and validated in a minimum viable data space that follows the implementations and deployments defined under the EDC Framework, which is powered by the specifications of the Gaia-X AISBL Trust Framework and the IDSA Data space protocol. The consortium is composed of 10 interdisciplinary partners: 2 Research Organizations, 3 SMEs, 2 Large Entities, 2 NGOs and 1 Clinical partner with extensive experience and expertise to guarantee the correct performance of the activities and the achievement of the results.