The Linux Foundation today launched the LF Deep Learning Foundation, an umbrella organization for open source development in artificial intelligence (AI), machine learning, and deep learning.

The founding members of LF Deep Learning are Amdocs, AT&T, B.Yond, Baidu, Huawei, Nokia, Tech Mahindra, Tencent, Univa, and ZTE.

Arpit Joshipura, the executive director of the Linux Foundation Networking Fund, said the new LF Deep Learning Foundation is part of the organization’s Harmonization 2.0 efforts. Joshipura joined Linux in December 2016, and he’s been on a mission to “harmonize” all the various open source networking projects so they play well together. “Harmonization 1.0 was all about networking communities, both open source and standards,” said Joshipura. “Harmonization 2.0 is about how networking platforms affect adjacent systems.”

The first project within the LF Deep Learning Foundation is the Acumos AI Project. The Linux Foundation announced its intention to form the Acumos project in October 2017. Acumos AI contributors will work on the development of AI models and  workflows. Initial code for the Acumos project has been contributed by AT&T and Tech Mahindra. The code is now freely available for download.

The Deep Learning Foundation will also host the Acumos Marketplace, which packages various components as micro-services and allows users to export ready-to-launch AI applications as containers to run in public clouds or private environments.

In addition to the Acumos project, the foundation anticipates future project contributions from Baidu and Tencent, among others. Baidu’s EDL project enhances Kubernetes with the feature of elastic scheduling and improvement to the overall utilization of Kubernetes clusters. Tencent’s Angel project, a high-performance distributed machine-learning platform jointly developed by Tencent and Peking University, is tuned for big data. It is capable of supporting over a billion parameters.

The Linux Foundation expects the new umbrella foundation to bring in a wide variety of projects, including tool kits, inferencing engines, and infrastructure deployment projects that use cloud-native technologies to make deep learning accessible and scalable. The Deep Learning Foundation has not yet named an executive director.