NEWYORK, USA, Feb. 6, 2020. IBM and China’s leading digital bank WeBank jointly organized “Workshop on Federated Learning and Analytics (FL-IBM’20)” at IBM T.J. Watson Research Center. Experts and scholars from IBM, WeBank, Google, MIT, University of Minnesota and other institutions participated in the meeting. New methods of federated learning were shared by 9 invited speakers, and ideas were exchanged at the panel discussion on“Data Privacy and Regulatory Issues in AI: Enterprise and Customer Perspectives”.

As a new paradigm of distributed encrypted machine learning, Federated Learning(FL) enables all parties to build models jointly without sharing data, that is, to connect data silos without violating data privacy regulations. In the past two years, more and more researchers and enterprises have paid attention to Federated Learning. How to improve the efficiency and performance of FL? How to develop Incentive mechanism to attract more participants? How can FL be applied at a truly large scale? Current challenges faced by FL and the future direction of FL were discussed at the workshop.


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