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Cross-CPP has a sound presence in Data4AI Workshop in European Big Data Value Forum (EBDVF) 2018

Cross-CPP project was represented by the consortium partner Universidad Politécnica de Madrid (UPM), in the Panels for discussion about technical challenges around each Data4AI technologies hosted BDVA and PPP project coordinators representatives.



The workshop was attended by 40 participants, including representatives of industry, research institutes, as well as the European Commission and different public administrations. During the workshop a series of speeches have carried out to discuss and share views about how the advances towards Artificial Intelligence (AI) environments are also growing the appearance of shortcoming technical barriers in different technology applications of AI.


Initially, the workshop concentrates in the identification of the main societal and technical challenges that the Industry is facing to have a full roll-out of Data driven Artificial Intelligence (AI) technologies in real-life environment scenarios.For that purpose, Big Data Value Association (BDVA) presents their position statement paper on “Artificial Intelligence for European Economic Competitiveness and Societal Progress” which clearly express how the combination of a wide range of technology applications would boost the adoption of AI solutions in the market by overcoming the main societal (ethical, regulatory, legal, etc.) and technical surrounded challenges data-driven AI. Those technical challenges come from the different set of AI Technology applications listed as follows: Advanced data analytics, Hybrid AI, Distributed AI / Edge Analytics, Hardware optimized to AI and Multi-lingual AI.


Finally, given the initial research work done and results obtained in Cross-CPP surrounded the Analytics Toolbox component, UPM presented to the audience which are the main challenges of Cross-CPP when trying to integrate mass data source analytics approach in a B2B Data-Marketplace mainly concentrating in addressing the following technical challenges of Advance Analytics and Hybrid AI Technology applications: a) Data anonymization b) Data Aggregation and c) Data Analytics as a Service. Indeed, the final outcomes have been focus on widespread the main lessons learned and best practices obtained to foster the knowledge transfer among PPP projects and AI initiatives. The presentation can be checked here: Cross-CPP-EBDVF18-Workshop on AI

Ultimately, Cross-CPP, and the rest of participants, have contributed with the outcomes of the workshop to the BDVA Position Statement Paper, and to extend its content about potential challenges and solutions on each of the core technologies identified for Data4AI.

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