{"id":32095,"date":"2026-07-16T16:10:24","date_gmt":"2026-07-16T14:10:24","guid":{"rendered":"https:\/\/www.ifabfoundation.org\/?post_type=project&p=32095"},"modified":"2026-07-25T12:09:47","modified_gmt":"2026-07-25T10:09:47","slug":"genf-federated-learning-as-a-service-flaas-with-generative-ai","status":"publish","type":"project","link":"https:\/\/www.ifabfoundation.org\/en\/project\/genf-federated-learning-as-a-service-flaas-with-generative-ai\/","title":{"rendered":"GenF: Federated Learning as a Service (FLaaS) with Generative AI"},"content":{"rendered":"

National Centre for HPC, Big Data and Quantum Computing (ICSC), a project funded by the European Union \u2013 NextGenerationEU \u2013 and by Italy’s National Recovery and Resilience Plan (PNRR) \u2013 Mission 4, Component 2.<\/strong><\/p>\n

Objectives<\/strong><\/h3>\n

The main goal is to extend FLaaS by improving peer-to-peer learning capabilities. This goal can be achieved by leveraging the transformative potential of generative AI to promote a distributed learning strategy that is both privacy-preserving and data-driven.<\/p>\n

Initial challenge<\/strong><\/h3>\n

Improving the state of the art in privacy-preserving generative AI and FL. After gaining an overview of the most effective methods for privacy-preserving data synthesis, the project aims to integrate generative AI into the FLaaS prototype.<\/p>\n

Solution<\/strong><\/h3>\n

The integration of generative AI results in an advanced FLaaS prototype: this will give the prototype improved and more effective capabilities for privacy-preserving distributed learning.<\/p>\n

Benefits<\/strong><\/h3>\n

Some expected outcomes are:<\/p>\n