Federated learning method, apparatus, and system

A federated learning method, applied to a second node in a federated learning system, wherein the method comprises:

• receiving, by the second node, a first query message from a first node, wherein the first query message indicates a target data feature required by a training task;
• sending, by the second node, data distribution information to the first node based on the target data feature, wherein the data distribution information indicates a data class of service data that is locally stored in the second node and that satisfies the target data feature;
• receiving, by the second node and from the first node, an indication to train a target artificial intelligence (AI) model;
• training, by the second node as indicated by the first node and by using stored target service data that belongs to a target data class, the target AI model corresponding to the target data class, to obtain an updated AI model;
• and
• sending, by the second node, the updated AI model to the first node.

A federated learning apparatus, comprising a processor, wherein the processor is coupled to a memory, the memory is configured to store a program or instructions, and when the program or the instructions are executed by the processor, the apparatus is enabled to perform:

• obtaining data distribution information of the plurality of second nodes based on a target data feature required by a training task, wherein data distribution information of any second node indicates a data class of service data that is both locally stored in the second node and that satisfies the target data feature;
• selecting at least two target second nodes from the plurality of second nodes based on a target data class required by the training task and the data distribution information of the plurality of second nodes, wherein the at least two target second nodes locally store target service data that satisfies the target data feature and that belongs to the target data class;
• and
• indicating the at least two target second nodes to perform federated learning, to obtain a federated learning model that is in the training task and that corresponds to the target data class.