Participants

This section describes the roles played by various participants in AI Arena.

Training Nodes

Training nodes are responsible for training models and are required stake tokens to be eligible. This requirement ensures a commitment to the network’s integrity and facilitates a distributed, trust-based mechanism for task assignment. This stake acts both as a gatekeeper to maintain a high standard and as a foundational element in the network’s security protocol, ensuring that nodes have a vested interest in proper execution and the overall health of the ecosystem.

Validators

Validators are responsible for evaluating work done by training nodes, submitting validation scores that influence reward distribution. They participate by staking tokens, which grants them the opportunity to validate tasks assigned to them, ensuring hardware compatibility and fair task distribution proportional to their stake. Upon completion of a task, they can withdraw heir stake and claim rewards, which are calculated based on their performance and adherence to the expected outcomes. The design ensures that validators are incentivised to provide accurate and honest validations, thereby maintaining the quality and reliability of the network’s computational tasks.

Delegators*

Delegators contribute to the FLock system by supporting other participants’ staking process, enhancing the network’s validation capacity without directly participating in the task training or validation process. They provide stake tokens to other participants, thereby increasing the delegatees’ potential to be selected for task assignments and influencing the overall reward distribution mechanism. Delegators share in the rewards earned by their associated delegatees, based on predefined algorithms that account for their staked contribution. This role allows individuals to participate in the network’s training, validation and economic activities, leveraging their tokens to support delegatees, without needing the technical capabilities to train or validate tasks themselves. Note that training nodes and validators who choose to accept delegation are free to choose a reward share ratio. The higher the ratio, the bigger the reward share their delegators will receive.

*Note that the delegation function may not be available in some regions due to local regulations.