Abstract: The list of 2019 CCF Science Technology Award is published. WeBank’s AI team won the “2019 China Computer Federation (CCF) Science Technology Award” by “the research and application of federated learning technology system” project.


Recently, the list of “2019 CCF Science Technology Award” is published. WeBank’s AI team won the “2019 China Computer Federation (CCF) Science Technology Award”, which represents the highest recognition in the field of computer science in China.

The science and technology award of the China Computer Federation (CCF) is important in the field of computer science. The CCF science and technology award committee organizes the selection. The purpose is to reward the outstanding achievements of technology research, technology development, technology innovation, application promotion in computing and relevant fields. The CCF award is divided into three categories. The technology innovation award is for significant discovery, invention, original innovation in the fields of computer science, technology and engineering, as well as the outstanding achievements that have great influence in the world.



It is reported that the WeBank’s AI team has proposed a complete and feasible federated learning solution to the problem of data islands in heterogeneous information networks. As a distributed machine learning technology, federated learning ensure that parties can jointly build models and improve the performance of machine learning under the premise of keeping parties’ data in local storage and data independence. It can achieve a win-win situation while meeting the needs of user privacy protection and data security.

In addition to studying the theory, WeBank’s AI team self-develop and publish the world’s first industrial-level open-source framework Federated AI Technology Enabler (FATE) based on federated learning technology. As a security computing framework based on the data privacy protection, FATE support federated learning structure system and security calculation of all kinds of the machine learning algorithm. It implements secure computing protocols based on homomorphic encryption and multi-party computing. It also helps multi-organization and institutions to cooperate effectively in data using and joint modeling under the premise of data security and government regulation.

Undoubtedly, federated learning technology has made large-scale inter-industry and cross-industry AI collaboration possible. WeBank’s AI team devote to build a more open and efficient AI cooperation ecosystem. They promote the development of AI technology and the application of data security and user privacy protection. Now, federated learning technology has successfully applied in intelligence risk control, intelligence equity pricing, intelligence retail, intelligence labor, anomaly detection and other business scenarios, helping upgrade the intelligence city, intelligence finance and multi-industries fields.

The innovation of new technology and new demand will help develop the AI industries. Undoubtedly, federated learning technology is the cornerstone of AI innovation in the future. Based on federated learning technology, multi-industries, multi-companies and multi-institution jointly building the federated learning ecosystem will be a new direction of the AI industry in the future. For this, Qiang Yang professor, the project leader, the CAIO of WeBank, said: “The global intelligence development enters a new stage. The new generation of machine learning algorithm framework should be based on privacy protection and security compliance, using the transparent mechanism to guarantee the healthy development of AI. Federated learning technologies is an urgently needed idea in all areas of the industry.