Federated Inference: Toward Privacy-Preserving Collaborative and Incentivized Model Serving

Researchers introduce Federated Inference (FI), a new collaborative paradigm where independently trained AI models can work together at inference time without sharing data or model parameters. The study identifies key requirements including privacy preservation and performance gains, while highlighting system-level challenges that differ from traditional federated learning approaches.