Introduction

The subnet template is a P2P coordination layer to deploy clusters of nodes that communicate in a decentralized network. Your job is to build the distributed AI application logic on top of it.

There are three main facets for building a decentralized AI subnet:

Application

This is the business logic for each peer and can be made to be role-isolated. Peers or roles have specific tasks; this is where that logic lives. For example, a peer can be responsible for generating inference, validating trainer peers, etc.

The application logic is deployed from the server.

Communication

This is how peers communicate with one another. There are two main features for peers to communicate with one another: using a GossipSub or direct P2P communication via custom protocols or the API protocol.

Consensus & Scoring

The consensus mechanism is for scoring peers. Each peer needs to know the scores of each other peer. On each epoch, a validator from the subnet will be randomly elected for an attestation-based consensus mechanism, where this validator submits scores for each peer in the subnet. The other peers can vote on that proposal by attesting to it; not attesting to it counts as a non-vote. The subnet must reach a consensus of >66% to generate emissions.