Dear all, As promised, I am providing you with some info on the new two projects that we are starting officially from September: i4Trust and ALMA. The following info is publicly available and has been given this way to the BoD for some better insight: *i4Trust (EU proposal 951975) Incubator of Trusted B2B Data Sharing ecosystems of collaborating SMEs linked to Digital Innovation HubsTotal funding: 5,8 million €, FIWARE Foundation part 4,3 million (of this 3,1 million cascade funding to third parties) €; FIWARE Foundation role: coordinator (1/3)About:i4Trust contributes to break "data silos" and stimulate sharing, re-using and trading of data assets by launching an "incubator of Trusted B2B Data Sharing ecosystems of collaborating SMEs linked to Digital Innovation Hubs", enabling these ecosystems to share data by implementing iSHARE, CEF Building Blocks and FIWARE, thus boosting the participation of SMEs in different sectors sharing data across value chains, resulting in a significant increase in amount of data shared, and breaking silos. i4Trust value proposition will contribute to build trust with data users and data suppliers by supporting 32 Bottom Up Experiments that will involve at least 150 SMEs and 32 Digital Innovation Hubs. The project will help them in understanding the demand for data, establishing data sharing partnerships, identifying concrete use cases about what can be done with the data, and adopting user-friendly tools already proved to be key success factors for B2B data sharing such as iSHARE, FIWARE, and CEF Building Blocks, the enablers for B2B Data Sharing that cover operational, legal, technical and governance aspects related with B2B Data Sharing. The project execution relies on a LEAN consortium of experts in B2B Data Sharing with deep roots in the European DIH Network. The project coordinator, FIWARE FOUNDATION, is linked to a network of European FIWARE iHUBs, they also bring a deep expertise in FIWARE and CEF Building Blocks technologies. FundingBox Accelerator – European leader in Financial Support to Third Parties – is also member of 6 DIH and partner of another 37 all across Europe. INNOPAY, implementation partner of iSHARE Foundation, brings to the project a deep knowledge in operational, technical, legal and governance issues related to B2B Data Sharing they have accumulated during the research and development process related with the launch of iSHARE, a neutral trust network, with high international acknowledgement and uptake. ALMA (EU proposal 952091) Human Centric Algebraic Machine LearningTotal funding: 4 million €, FIWARE Foundation part 237,750.- €; FIWARE Foundation role: participant (1/9)About:Algebraic Machine Learning (AML) has recently been proposed as new learning paradigm that builds upon Abstract Algebra, Model Theory. Unlike other popular learning algorithms, AML is not a statistical method, but it produces generalizing models from semantic embeddings of data into discrete algebraic structures, with the following properties: P1: Is far less sensitive to the statistical characteristics of the training data and does not fit (or even use) parameters P2: Has the potential to seamlessly integrate unstructured and complex information contained in training data, with a formal representation of human knowledge and requirements; P3. Uses internal representations based on discrete sets and graphs, offering a good starting point for generating human understandable, descriptions of what, why and how has been learned P4. Can be implemented in a distributed way that avoids centralized, privacy-invasive collections of large data sets in favor of a collaboration of many local learners at the level of learned partial representations. The aim of the project is to leverage the above properties of AML for a new generation of Interactive, Human-Centric Machine Learning systems., that will: - Reduce bias and prevent discrimination by reducing dependence on statistical properties of training data (P1), integrating human knowledge with constraints (P2), and exploring the how and why of the learning process (P3) - Facilitate trust and reliability by respecting ‘hard’ human-defined constraints in the learning process (P2) and enhancing explainability of the learning process (P3) - Integrate complex ethical constraints into Human-AI systems by going beyond basic bias and discrimination prevention (P2) to interactively shaping the ethics related to the learning process between humans and the AI system (P3) - Facilitate a new distributed, incremental collaborative learning method by going beyond the dominant off-line and centralized data processing approach (P4) * It has not yet been defined within the BoO when the internal (prep) work will start and who will be doing what. Cheers, Cristina Cristina Brandtstetter Chief Marketing Officer M. +39 3737004468 cristina.brandtstetter at fiware.org www.fiware.org <https://twitter.com/fiware> <https://twitter.com/fiware> <https://www.fiware.org/events> The 8th FIWARE Global Summit <https://www.fiware.org/wp-content/uploads/2020/03/FIWARE-Global-Summit-2020_Brochure.pdf> Will Be Bigger & Bolder Than Ever! Don't miss out. Watch the Summit video <https://www.youtube.com/watch?v=t_r7zPc-PwA&feature=youtu.be> & get your ticket here <https://www.eventbrite.com/e/fiware-global-summit-malaga-2020-tickets-84918009051> ! -------------- next part -------------- An HTML attachment was scrubbed... URL: <https://lists.fiware.org/private/ff-marketing/attachments/20200421/36144e41/attachment.html>
You can get more information about our cookies and privacy policies clicking on the following links: Privacy policy Cookies policy