The I4MS program in H2020 has been and is a great success for the Digital Transformation of European Manufacturing SMEs. Phase IV of the program was focussing on DIHs and on highly innovative technologies like Digital Twins and AI. In particular, the AI REGIO Innovation Action developed a virtuous alliance between Regions, DIHs, AI solution providers and Manufacturing SMEs, which is materialised by a new methodology for DIHs service portfolio and customer journey analysis, an AI4EU -oriented toolkit of Data and AI resources, a network of Didactic Factories and their TEchnology and REgulatory SAndboxes (TERESA) and an ecosystem of SME-driven experiments and their Digital Transformation pathways. It is time now to align such important outcomes to the evolution of Manufacturing towards Industry 5.0, the evolution of cloud AI Technologies to AI-at-the-Edge, the evolution of H2020 to Horizon and Digital Europe programmes e.g. to EDIH, Data Spaces and AI TEFs (Testing and Experimentation Facilities) for Manufacturing. Some of the AI REGIO I4MS Phase IV motivations are now evolved: it is time for AI REDGIO 5.0 for keeping momentum of AI technologies adoption in Manufacturing SMEs. AI REDGIO 5.0 aims at renovating and extending the H2020 I4MS AI REGIO alliance between Vanguard EU regions and DIHs for a competitive AI-at-the-Edge Digital Transformation of Industry 5.0 Manufacturing SMEs. AI REGIO outcomes (methods and tools for DIHs governance and cross-DIH collaboration; Data Space and AI for Manufacturing toolkit; Didactic Factories network and TERESA facilities; SME-driven experimentations in 14 Vanguard regions) will be i) extended to the I5.0 principles; ii) enabled by the newest trusted technologies along the edge-to-cloud continuum; iii) supported by European open source hw/sw reference implementations, preserving EU values and ethical principles; iv) interconnected with the EDIH network in DEP as well as with the AI TEF nodes and the Data Spaces deployment program.

In parallel to the current developments in the so-called narrow artificial intelligence (AI) realm, there is an urgent demand for more universal, general AI approaches that can operate across a wider spectrum of application domains with varying data characteristics. It is expected that the emerging sustainable AI methods can be efficiently deployed in the edge-cloud continuum on different hardware platforms and computing infrastructure depending on the real-world task scenarios and constraints including the limited energy budget. In response to this growing demand and emerging trends we propose to adopt a brain-like approach to AI system design due to its promising potential for functional flexibility, hardware friendliness as well as energy efficiency among others. To this end, EXTRA-BRAIN is aimed at developing a new generation of AI solutions based on brain-like neural networks that enable us to overcome key limitations of the current state-of-the-art methods, exemplified by deep learning, such as limited cross-task generalisation and extrapolation to novel domains (bounded reliability), excessive dependence on costly annotated data as well as extensive training and validation processes with heavy demand for compute resources at high energy cost, to name a few. The core brain-like neural network design in our approach derives from the accumulated computational neuroscience insights into the brain's working principles of information processing, key learning schemes and neuroanatomical structures that underlie the brain's perceptual/cognitive phenomena and its functional flexibility. Furthermore, these novel models are supported by data optimisation pipelines, which improve data quality, security and reduce the costs of assembling suitable training data, and an explainability framework to empower the human user. The proposed EXTRA-BRAIN framework will be examined in a diverse set of use cases with different hardware demands in the edge-cloud continuum.

CLIMINVEST is joint effort of sustainability experts and finance/investing experts to improve the bankability of climate adaptation solutions. In this direction, the project will develop, integrate and validate tools and techniques that will empower climate adaptation stakeholders to develop “bankable-by-design” (BbD) projects with a positive ROI, including projects that are continually assessed in order to proactively identify and remedy issues that can affect their bankability. Moreover, CLIMINVEST will facilitate private investors to assess them, and to include them in their portfolios and ESG strategies. Based on the project’s BbD framework, local/regional governments and operators of climate-adaptation solutions will greatly benefit from CLIMINVEST techniques and blueprints for developing and deploying bankable solutions that can be integrated with broader projects and deliver co-benefits in conjunction with other climate mitigation efforts. Furthermore, CLIMINVEST will provide investors with risk assessment and ESG reporting tools for projects with climate adaptation elements towards lowering the barriers that hinder their engagement in climatic adaptation projects. CLIMINVEST will develop and offer a marketplace of bankable climate adaptation projects and solutions, which will boost the discoverability of “best practice” solutions, while also facilitating their replication, repurposing and wider use. The project will build a vibrant ecosystem of interested stakeholders around this marketplace, including local/regional governments, sustainability experts, private investors, and policy makers. The project’s platform and associated ecosystem will serve as a basis for the exploitation, sustainability and wider use of the project’s results. In this direction, the project will devise and validate models for the monetization of services of the project’s marketplace.