Coordination of AI sectorial testing and experimentation facilities

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(DIGITAL-2023-CLOUD-AI-04-COORDINATEF) - COORDINATION OF AI SECTORIAL TESTING AND EXPERIMENTATION FACILITIES

Programme: Digital Europe Programme (DIGITAL)
Call: Cloud, Data and Artificial Intelligence EU

Topic description

ExpectedOutcome:

  • Action plan organised along different domains: technological, business models, skills development, dissemination, legal aspects, outreach, etc., to develop links and synergies with EDIHs, data spaces, edge AI TEF, network of AI research excellence centres, and the AI-on-demand platform.
  • A catalogue of common resources and services across the TEFs.
  • Joint dissemination and communication plan with TEFs on their activities and services, to be implemented within the project duration.
  • A specialised support unit to coordinate co-funding instruments, including regular interactions with Member State’s administrations, including with regards to Grant Agreements.
  • Technical mechanisms for a seamless exchange of assets with the AI-on-Demand platform. Delivery of individual and targeted sectorial sections within the platform (distributed model).
  • A specialised business consultancy unit focussing on business and go-to-market strategy, optimising TEF business sustainability.
  • Periodic impact assessment and road-mapping: collection and analysis of the key performance indicators (KPI) defined for the TEFs and sharing of good practices and lessons learnt.
Objective:

The Coordination and support action grant will support the sectorial Testing and Experimentation Facilities (TEFs) created under the WP 2021-2022 (Health, Manufacturing, Agri-Food, Smart Cities and Communities) and the future new ones to be create under the Digital Europe Programme, to develop complementary cross-TEF activities in providing AI services from a cross-sector perspective, to maximise the overall impact of TEFs in their ambitions of achieving world-class excellence and help the sectorial TEFs to better link with relevant EU projects, initiatives and stakeholders in the AI ecosystem of excellence. By boosting the reinforcing feedback loops, the CSA will also bolster the sectorial TEF’s and the ecosystem’s sustainability.

Once the sectorial TEFs funded under the 2021 call are established, it is necessary to coordinate the TEFs with other actions launched in the Digital Europe Programme (in particular data spaces, the edge AI TEF, the AI-on-demand platform, relevant cloud and HPC initiatives) and to develop a strong ecosystem around the TEFs enabling a faster and growing adoption of AI technologies in the European market.

Scope:
  • The CSA will help develop synergies and exchanges between the TEFs, and with other relevant projects, such as the European Digital Innovation Hubs (EDIHs), data spaces, network of excellence research centres, and other actions funded e.g. under DEP and Horizon Europe, AI-on-demand platform, and the community at large.
  • It will establish strong links with Edge to Cloud and relevant HPC actions funded under strategic objective 1 (EuroHPC JU), using when appropriate the SIMPL platform as a connector, and help TEFs to make the most out of all these resources and services.
  • It will support the running projects in allowing economies of scales regarding common activities run by the individual networks (e.g., organization of events, access to common resources, mentoring and exchange mechanisms among TEFs, integration with 3rd party services and other EU funded projects, etc.) and exchanges of best practices to reinforce and optimize cooperation.
  • It will support TEFs to help companies using their services to comply with the AI Act. This could be through regulatory sandboxes, standards, certifications, labelling schemes, research methodologies for the explainability of AI systems and collaboration with public authorities, depending on what TEF themselves offer and what additional or complementary support to the companies is needed.
  • It will support TEFs in their dissemination activities towards industry, users and public administrations. Special attention should be on coordinating mentoring and twinning programmes for innovators in order to foster fair participation and potential expansion of TEFs activities across Europe to complement and reinforce the on-going TEFs. It should contribute to the visibility of AI & robotics in Europe, building on technologies tested in TEFs and targeting sectorial audiences, with a clear focus on real world applicability.
  • Support and coordination with regards to co-funding instruments, helping TEFs in common approaches towards Member States including support and exchange of best practices in the implementation and reporting requirements imposed by state-aid rules, contractual requirements, interpretation of the Grant Agreements etc.
  • Act as facilitator for cooperation with the AI-on-demand platform. Foster contribution from TEFs and channelling TEFs needs towards the AI-on-demand platform.
  • Facilitate coordination with the edge AI TEF. Solutions developed and tested in the former could be later integrated and tested in the sectorial TEFs.
  • The CSA will establish the necessary resources to help and support TEFs in their coordinated go-to-market approach, including but not limited to sustainability plans, sale strategies, price lists, etc.
  • Facilitate exchanges with EDIHs and national competence centres, etc. to maximise the opportunities offered e.g., to maximise the outreach to all regions across Europe).
  • Support the European Commission in the monitoring of existing TEFs, assessing progress and providing recommendations for their implementation and drawing lessons for policy-making.
  • Targeted stakeholders: The consortium should include a relevant representation of all the sectorial TEFs selected from the 1st call of the Digital Europe Programme, to ensure that the selected CSA optimally support their coordination. These organisations will be subject to Article 12(6) of Regulation (EU) 2021/694.

Keywords

Internet Services & Applications Big data Algorithmic auditability and accountability Cloud Services Digital Services and Platforms Sensing Signal interpretation Artificial intelligence Vehicular Systems (e.g. autonomous vehicles) Internet of Things, embedded/pervasive systems Technologies and Use Cases Dimension Localisation Trust in decision making algorithms Data value chains Network technologies / Internetworking Artificial intelligence, intelligent systems, mult Machine learning, statistical data processing and Mapping Motion planning Cloud, Edge and Virtualisation

Tags

AI data spaces AI tools Artificial Intelligence AI resources standarisation Testing and Experimentation Facility IoT living labs public administration ethical AI digital marketplace trustworthy AI pollution sandboxing mobility pilot Digital platform robotics TEF AI solutions

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