Decentralised and Sustainable AI Processing
Funds two €17.5M research projects that spread AI processing across sustainable, secure edge, cloud and HPC resources.
Centralised AI infrastructure is running into limits in energy, compute capacity, chip availability, data quality, security and latency. This topic funds research into a different model: AI data processing distributed across edge, cloud and high-performance computing resources throughout collection, training, fine-tuning and deployment.
Projects can go beyond conventional federated learning with …
A Research and Innovation Action for decentralised, federated and sustainable AI data processing across the cloud-to-edge compute continuum. Projects can develop distributed architectures beyond federated learning, workflows across heterogeneous infrastructure, model compression, data-quality and consistency tools, privacy-preserving distributed management, post-quantum protection, and end-to-end energy and sustainability monitoring. Each proposal must demonstrate its approach in at least two complementary real-world use cases in different domains, starting at TRL 3 and reaching TRL 6-7.
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