New approaches for decentralized, federated and sustainable AI data processing (RIA)

What is this call about?

The topic funds research on decentralised, federated and energy-efficient AI data processing across the edge, cloud and high-performance computing continuum. It targets consortia able to demonstrate results in at least two use cases.

What does this call fund?

Scope

The topic funds technologies that let AI data processing use distributed compute resources across the cloud and edge continuum throughout the whole AI model lifecycle, from data collection to training, fine-tuning and deployment. The aim is to help overcome Europe's AI compute capacity bottlenecks with decentralised and sustainable alternatives to centralised AI computing.

Research areas

• Distributed, decentralised and federated AI architectures beyond federated learning, including model compression and scaling across diverse infrastructures.
• AI workflows across edge, cloud and high-performance computing, possibly including neuromorphic and quantum computing and hardware efficiency improvements such as in-memory computing.
• Methods to improve data availability, quality and consistency across distributed sources, optimise data transfers and protect privacy, for example with post-quantum cryptography.
• Tools to measure, monitor and improve end-to-end energy efficiency and sustainability of AI data processing.

Use cases

Projects should demonstrate their results in at least two complementary use cases in different domains, relevant to sectors critical for Europe's competitiveness.

Technology readiness

Activities start at TRL 3 and reach TRL 6-7.

When is the deadline?

18 March 2027 (133 days)

18 March 2027 (single-stage submission).