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Date
19.01.2024 | 10:00 - 10:20 (CET)

The AIoD: The European AI On-Demand Platform and Ecosystem

The AIoD platform aims to facilitate the sharing of AI resources, including datasets, algorithms, and software artifacts, as well as computational resources. These assets and computational resources adhere to a unified conceptual schema and governance model, promoting the reproducibility and reuse of AI research findings. The platform is designed to be extensible, allowing the research community to develop and incorporate additional services as needed. AI4Europe is one of the projects, funded under the Horizon Europe programme, that is responsible for the management, development and facilitation of the AI-on-Demand Platform (AIoD).

The XIth Edition of the BIFI International Conference 2024, hosted at the Institute for Bio-computation and Physics of Complex Systems, at the University of Zaragoza, will gather under the same umbrella a wide variety of leading scientists working in an array of fields in Physics, Biology and Statistics where the development and applications of AI and ML-based Methodologies are pivotal. All topics broadly related to AI and ML applications in these disciplines are welcome to the meeting, where scientific contributions will be organized according to the following tracks: AI: Methods and Applications, AI and Statistical Modelling, AI Applications in Physics, and AI Applications in Biomedicine.

AI4Europe is one of the projects, funded under the Horizon Europe programme, that is responsible for the management, development and facilitation of the AI-on-Demand Platform (AIoD). AI4Europe was invited to present the AIoD platform within the BIFI Conference. The talk will be on Friday 19 January. During the talk, an overview of the AIoD platform will be provided, including its purpose, objectives as well as a general perspective of the AIoD architecture. The AIoD platform aims to facilitate the sharing of AI resources, including datasets, algorithms, and software artifacts, as well as computational resources. These assets and computational resources adhere to a unified conceptual schema and governance
model, promoting the reproducibility and reuse of AI research findings. The platform is designed to be extensible, allowing the research community to develop and incorporate additional services as needed.

Speakers

Rafael Tolosana-Calasanz