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European Network of AI Excellence Centres: Expanding the European AI lighthouse (RIA)

To ensure European open strategic autonomy in critical technology such as AI, with huge potential socio-economic impact, it is essential to reinforce and build on Europe’s assets in such technologies, including its world-class researcher community, in order to stay at the forefront of technological developments.

As stated in the communication from the European Commission on Artificial Intelligence for Europe and the coordinated action plan between the European Commission and the Member States, while Europe has undeniable strengths with its many leading research centres, efforts are scattered. Therefore joining forces will be crucial to be competitive at international level. Europe has to scale up existing research capacities and reach a critical mass through cross-community networks of European excellence centres in AI. Proposals should develop mechanisms to reinforce and strengthen the networks of excellence centres in AI. They are expected to bring the best scientists from academia and industry together to join forces in addressing the major AI challenges hampering its deployment, and to reinforce excellence in AI throughout Europe via a tightly-coupled network of collaboration.

Such networks are expected to mobilise select groups of key researchers from both industry and academia to collaborate on solving significant AI problems in which Europe has exceptional expertise. The networks are expected to increase the impact of the funding by making faster and greater progress through the joint efforts by recognised leaders working together, drawing on both shared and complementary perspectives, such as reasoning and learning, on the chosen problems. Such networks, together with other mechanisms, will play an important role in achieving a critical mass of talent and in overcoming the present fragmentation of AI research in Europe.

Proposals will mobilise the best European teams in AI community to join forces to address major technical as well as sector- or societal-driven challenges: strengthening excellence, networking, multidisciplinarity, academia-industry synergies.

This initiative contributes to the initiative started in H2020 to develop a vibrant European network of excellence centres in AI, and a vibrant AI scientific community, and continued in the first call of Horizon Europe. To complement and extend this initiative the proposals should create a network of excellence for the following topics:

  1. Next Generation AI – covering foundational research and emerging and novel approaches, with a view of improving the technical performances of AI-based systems, such as increased accuracy, robustness, verifiability, dependability, adaptability, versatility, graceful degradation, etc. Research is also expected to address functional and performance guarantees.Aspects to be covered include, but are not limited to: foundational research in artificial intelligence and machine learning including new paradigms, algorithms, architectures and novel optimization and regularization methods, hybrid AI, hybrid machine learning, data/sample –efficiency.
  2. Scientific research and technologies prioritised in the latest SRIDA (Strategic Research, Innovation and Deployment Agenda of the AI, Data and Robotics PPP) , and complementing the previously selected Networks of Excellence centres (either in H2020-ICT48, or the first calls for Networks of Excellence Centres in Horizon Europe).

Proposals will need to demonstrate how they complement, intend to expand and maximise the coverage of the previously selected[[ the earlier Networks of Excellence centers projects result from the topics H2020-ICT-48, as well as the first topics of Horizon Europe HORIZON-CL4-2021-HUMAN-01-03 and HORIZON-CL4-2021-DIGITAL-EMERGING-01-12]] networks of excellence centres in AI.

To develop the lighthouse the selected networks should identify the major strength Europe has on a number of specific AI topics, and gather the best teams working on them in Europe in a strongly connected virtual institute, collaborating and competing to progress on these topics. They might also identify topics where Europe needs support to become competitive at international level, if strategically important.

Each network should set ambitious challenges, with the overarching aim of becoming aworld reference of excellence in AI on the strategic topics prioritised by the Network. As a result, Europe’s diversity will stimulate healthy competition, rather than the fragmentation of the AI community.

The scientific progress should be driven by major societal challenges, which will serve as a source of research questions. This should also make it attractive for industries to join the efforts, in bringing their top research teams in the network, and also provide data/challenges that can become reference to drive scientific progress.

Composition of the Networks:

  • Proposals should be driven by leading researchers in AI and AI relevant technologies from major excellent AI research centres, and bringing the best scientists across Europe, including also from promising research labs. They will bring on board the necessary level of expertise and variety of disciplines and profiles to achieve their objectives, ensuring a multidisciplinarity and multi-sectorial research approach, while respecting equality and diversity among the attracted talents.

Activities of the Networks:

  • In order to structure the activities, the proposals will focus on important scientific or technological challenges with industrial and societal relevance where Europe will make a difference, by building on existing strengths, or increasing strength in areas that are critical for Europe.
  • Based on the identified challenges, the networks should develop and implement common research agendas. The main vision and roadmap with clear targets, as well as methodology to implement and monitor progress will have to be specified in the proposal and can be further developed during the project.
  • Scientific progress will have to be demonstrated through testing on application specific datasets or use-cases that characterise a demonstrated need of individuals or society as a whole. By extending the benchmarking of foundational research to application specific areas, the research community will simultaneously address advancements in AI and grand societal and technological challenges.
  • The networks should define mechanisms to foster excellence throughout Europe, to increase efficiency of collaboration, including through networking and exchange programmes, and to develop a vibrant AI network in Europe.
  • The networks are expected to disseminate the latest and most advanced knowledge to all the academic and industrial AI laboratories in Europe and involving them in collaborative projects/exchange programmes. (This could involve projects defined initially or via financial support to third parties, for maximum 20% of the requested EU contribution, with a maximum of 60k€ per third party[[ Maximum amount per third party, received from a given Action, over its entire duration]]).
  • Furthermore, it is key that each network provides a dissemination plan on how it intends to promote uptake by disseminating resources, e.g. datasets, software, or toolkits that are required to replicate and validate any experiments that gave rise to this knowledge.
  • The networks should develop interactions with the industry, in view of triggering new scientific questions and fostering take-up of scientific advances
  • The networks will develop collaboration with the AI-on-Demand platform, the AI, Data and Robotics Partnership and with relevant Digital innovation Hubs and AI start-up initiatives, to disseminate knowledge and tools, and understand their needs.
  • The networks should also foster innovation and include mechanisms to exploit new ideas coming out of the networks’ work (for instance via incubators).
  • Overall, each network will define mechanisms to become a virtual centre of excellence, offering access to knowledge and serve as a reference in its chosen specific field, including activities to ensure visibility.

The proposals should

  • include mechanisms to spread the latest and most advanced knowledge to all the AI-labs in Europe
  • develop synergies and cross-fertilization between industry, academia and civil society.
  • become a common resource and shared facility, as a virtual laboratory offering access to knowledge and expertise and attracting talents
  • provide broad access to AI excellence in Europe and also play an important role in increasing visibility
  • provide access to the required resources and infrastructure to support the R&D activities of the action, such as cloud and computing capacity, IoT, robotics equipment, support staff and engineers, where relevant, and the capacity to develop prototypes, pilots, demonstrators, etc.
  • include a number of major scientific and application challenges which will mobilise the community to join forces in addressing them. Continuous evaluation and demonstration of scientific and technological progress (with qualitative and quantitative KPIs, benchmarking and progress monitoring processes) towards solving the targeted challenges will motivate the entire network and support publications and scientific career developments (providing reference benchmarks to publish comparative results, using the reference data, scenarios, etc.), and also showcase the technology in application contexts, to attract more user industries and foster take up and adoption of the technology.
  • include mechanisms to share resources, knowledge, tools, modules, software, results, expertise, and make equipment/infrastructure available to scientists to optimise the scientific and technological progress. To that end, proposals should exploit tools such as the AI-on-demand platform[[ Initiated under the AI4EU project https://cordis.europa.eu/project/id/825619 and further developed in projects resulting from H2020-ICT-49-2020 call]] and further develop and expand the platform, to support the network and sharing of resource, results, tools among the scientific community, maximising re-use of results, and supporting faster progress. Mechanisms to test results and continuously measure and demonstrate progress should be integrated in the platform, which is also important to support the scientific community, allowing also for comparative analysis. Openness and interoperability of components are encouraged to develop synergies and cross-fertilization between different approaches and solutions (e.g. through modularity of components or open interfaces)
  • include collaboration mechanisms among the best AI and AI-relevant research teams, but also mechanisms to bring all European AI teams to the highest level of excellence. This is also in view of supporting and encouraging the adoption of AI technologies in all Member States and Associated Countries, with particular emphasis on geographical aspect and elimination of gaps between Member States/Associated Countries, as well as addressing existing gender disparities.
  • exploit and develop technology enablers, such as methodologies, tools and systems and exploit latest hardware development and data spaces, cloud and HPC resources.

The networks will also address a number of sector- or societally-driven challenges, mobilising the community towards achieving common goals in addressing such challenges that AI can help overcome, demonstrating the positive impact on the society, economy and environment.

Activities are expected to achieve TRL 4-5 by the end of the project.

Proposals are expected to develop synergies:

  • With other Networks of excellence centres in AI funded in H2020 or Horizon Europe, with a view of, all together, create vibrant European network of AI excellence centres. To that end, the activities should integrate with and complement the activities of the H2020-ICT-48 projects. The proposals are expected to dedicate tasks to ensure this coherence.
  • With relevant activities in AI, Data and Robotics, primarily under destinations 3, 4 and 6, but also in other destinations and clusters, as well as relevant missions, and share or exploit results where appropriate.

All proposals are expected to allocate tasks to cohesion activities with the PPP on AI, Data and Robotics and funded actions related to this partnership, including the CSA HORIZON-CL4-2021-HUMAN-01-02.

Background

The selected networks of excellence centres will contribute to the larger objective of the European Commission to establish the European AI lighthouse.

The AI lighthouse is expected to mobilise the AI community to collaborate on key AI research challenges and to progress faster in joined efforts rather than working in silos, leading to fragmented and duplicated efforts. This is essential to reach critical mass and overcome the present fragmentation of AI research in Europe.

The lighthouse will bring together stakeholders from research, innovation and deployment, to become a world reference in AI that can attract investments and the best talents in the field. The lighthouse will build on key pillars, each of them being a network of excellence centres specialising in a given topic where Europe has the potential to become a global champion.