AI Society x WeBank | Demystify Federated Learning
April 26, 2022 @ 7:00 pm - 8:00 pm
Demystify Federated Learning
Date: Tues, 26, April
Time: 19:00-20:00 HKT
Venue: Zoom Event
(Meeting ID: 830 3487 7589 | Passcode: 738004)
About this event
AI works best with learning from sufficiently large curated data. However, there are concerns on user data privacy and data protection with existing machine-learning approaches of data centralization. Federated learning (FL)is a new branch in AI that has opened the door for a new era of machine learning.
FL is an emerging machine learning paradigm that enables multi party collaborative model training with the collaborated parties’ data resided locally – decentralised data. This new machine learning paradigm has the merit of no data sharing and thereby reducing privacy leakage while breaking data silos. Thus, it is able to provide a more personalized experience without compromising on user privacy.
Isaac Wong (Webank Principal AI solution architect) will breakdown the unique concept in Federated Learning like (Homomorphic encryption, Model aggregation) for the audience. He will use a real-life example to demonstrate how companies maximize the benefits of FL.