Sony patents method to pick nearby devices for shared AI training

1. An electronic device for federated learning, comprising: a transmitter; and a processing circuitry configured to: determine that a specific distributed node will be used to generate a global model parameter, wherein a correlation between local training data of the specific distributed node and local training data of other distributed nodes for generating the global model parameter meets a specific correlation requirement; and control the transmitter to transmit a local model parameter of the specific distributed node to a central processing apparatus, wherein the local model parameter is generated by the specific distributed node based on its local training data, and control the transmitter to transmit data collection information of the local training data of the specific distributed node to the central processing apparatus, wherein the data collection information is information used by the central processing apparatus to determine the correlation between the local training data of the specific distributed node and local training data of other distributed nodes that have been determined to be used to generate the global model the parameter, wherein the data collection information includes node locations of distributed nodes, wherein the specific correlation requirement includes the specific distributed node being outside associated exclusive regions of the other distributed nodes that have been determined to be used to generate the global model parameter, and wherein an associated exclusive region of a distributed node is defined by: a region in which the distance from each point of the region to the distributed node is less than an exclusive distance, or a set of a second predetermined number of distributed nodes closest in distance to the distributed node.