Compute-to-Data provides a means to exchange data while preserving privacy by allowing the data to stay on-premise with the data provider, allowing data consumers to run compute jobs on the data to train AI models. Ref: [[Confidential Computing]] Ocean Protocol Foundation (OPF) is working on a decentralized data marketplace where there is no middleman/custodian holding the data. Rather than having the data sent to where the algorithm runs, the algorithm runs where the data is. The idea is very similar to federated learning. The difference, McConaghy says, is that federated learning only decentralizes the last mile of the process, while Compute-to-Data goes all the way.