Our proposed solution is a subnetwork that incentivises Compute, Bandwidth and Latency. The compute helps power the training of a miner’s local version of a model and the bandwidth and latency helps power the averaging of each miners local model weights using an operation called butterfly all-reduce. Once this process is successfully completed, each miner has a unified global averaged gradient that it can use to update it’s model weights.