Federated Learning
Train AI models across the FractalAI network without sharing raw data. Privacy-preserving, decentralized machine learning.
Privacy-Preserving
Data never leaves the node. Only model gradients are shared. Full privacy guaranteed.
Distributed Training
Multiple nodes train FANE models simultaneously. Aggregated results improve the global model.
Cryptographic Verification
Gradient submissions are signed with Dilithium. Tamper-proof contribution tracking.
FRAI Rewards
Nodes that contribute quality gradients earn FRAI rewards proportional to their contribution.
How It Works
Global Model Distribution
The current FANE model weights are distributed to participating nodes.
Local Training
Each node trains on its local data. Raw data never leaves the node.
Gradient Submission
Computed gradients are signed and submitted on-chain.
Secure Aggregation
Gradients are aggregated using secure multi-party computation.
Model Update
The global FANE model is updated. All nodes receive the improved model.
Contribute Your Node
Run a FractalAI node to participate in federated learning and earn FRAI.
Get Started