Abstract: On June 18th, WeBank joined the OpenI Platform Council and released the “OpenI-Zongheng”project.
On June 18th of 2019, the new generation of the Artificial Intelligence Technology Innovation Strategic Alliance (AITISA) holds the 1st council meeting in Peng Cheng Laboratory. WeBank announces that it joins the council and technical committee and publishes the “OpenI-Zongheng” project.
OpenI platform (OpenIntelligence) is a new generation of open-source artificial intelligence platform under the leadership of the Ministry of Science and Technology of the People’s Republic of China. The platform is organized by AITISA and jointly maintained by industries, universities and research institutes. Major members include prestigious Chinese universities and leading companies in the industry. Members include Peking University, Tsinghua University, Zhejiang University, Beihang University, Xi ‘an Jiaotong University, University of Science and Technology of China, Nanjing University, Institute of Computing Technology Chinese Academy of Sciences, Baidu, Ali, Tencent, Huawei, Didi, SenseTime, Thomson, MEGVII. The platform already hosts many open source projects such as OpenI Octopus, OpenI Coral and Intelligence Trusie, all contributed by companies and institutions. The newly contributed “Open-Zongheng” project is a set of Federated Learning calculation tools by WeBank’s AI team. It is designed for the Federated Learning researchers. Complying with data security and legal requirements, “Open-Zongheng” can be used for multi-party data usage and joint modeling. As an important part of OpenI’s software environment, the “Open-Zongheng” project aims to establish an open environment for data collaboration.
Preservation of data security and information privacy is one of the biggest challenges when implementing AI technologies today. Federated Learning is a new distributed machine Learning technology. Its major drive is to allow participants to jointly train machine learning models without exposing the underlying data, participates jointly improving local model effect and achieving AI collaboration.
Xiang Cao, a senior researcher at the AI department of WeBank, introduced Federated Learning
Because of its great significance to break the data silos and further promote industrialization of artificial intelligence, federated learning has attracted much attention in recent years. The academia and industry alike are actively seeking methods to standardize and instrumentalize federated learning. In February this year, WeBank’s AI team open-sourced Federated AI Technology Enabler (FATE), the world’s first Federated Learning open source platform. It is a generic implementation of Federated Learning to facilitate promotion of Federated learning. Based on FATE, the “Open-Zongheng” project provides a convenient tool for fast experimenting iterative algorithms. It also includes abundant federated modeling algorithm components to meet most modeling needs. Instrumentalization is the first step to industrialization. This easy-to-use toolkit will lower the technology barrier and attract more participants and contributors.
Tianjian Chen, deputy general manager of WeBank’s AI department, said, “OpenI open-source platform is committed to building an open and inclusive AI ecosystem, while Federated Learning is an effective means to facilitate AI collaboration in today’s increasingly strict data privacy protection, I believe that “OpenI-Zongheng” project can build a bridge between institutions and promote the joint construction of open AI ecosystem.”