Going Deeper and More Distributed, Linux Introduces Two New Projects

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There seems to be no stopping the Linux Foundation these days, as their support of open source code and positively disrupting entire industries continues, this week with the announcement of two new projects: Angel and Elastic Deep Learning (EDL).

This comes at a time when the world’s largest telecom and technology companies are joining the Foundation and contributing substantial projects and source code; in the case of these latest projects, they surfaced as part of the LF Deep Learning Foundation, introduced in March of this year. LF Deep Learning is an umbrella organization to support open source innovation in AI, ML and deep learning.

AT&T and Tech Mahindra were among the founding members of Deep Learning and donated their Acumos AI project to get a big and growing party started. Acumos is a platform for the development, discovery and sharing of AI models and AI workflows, and is being leveraged by heavyweight co-founders Amdocs, Huawei, Nokia, ZTE, Tencent and Baidu.

Tencent and Baidu are taking the lead on Angel, a distributed machine learning platform and EDL.

The Angel Project from China’s Tencent is a distributed machine learning platform based on Parameter Server, running on YARN and Apache Spark. The announcement by the Linux Foundation explains that “Angel” substantially improves performance with big data, able to support higher dimension models with billions of parameters. The project already has more than 1,000 contributions from a wide range of developers, and its algorithms are available to data scientists and other developers who can create algorithms without writing any code.

EDL from Baidu was designed to help deep learning cloud service providers to build cluster cloud services and includes a Kubernetes controller and an auto-scaler which changes the number of processes of distributed jobs to the idle hardware resource in the cluster. EDL uses the Apache 2.0 license and like Angel has already received more than 1,000 contribution commitments.

“Angel shares a common goal with the LF Deep Learning Foundation: to make deep learning easier to use,” said Xiaolong Zhu, senior AI researcher at Tencent. “By becoming a part of the LF Deep Learning Foundation, we believe Angel will be more active in the open source community, accumulate more use cases, expand usage scenarios and actively cooperate with other partners. Angel will continue working on a consistent and continuous user experience to make deep learning technology easier to apply and develop.”

Tencent is one of the largest and fastest growing companies in the world, as the sixth largest Internet company in terms of revenue, topping $237 billion in 2017. Tencent Holdings Limited is a Chinese multinational investment holding conglomerate founded in 1998, whose subsidiaries specialize in various Internet-related services and products, entertainment, games, telecom and messaging services and more.

“We are excited to see that EDL has been accepted to LF Deep Learning Foundation,” said Yanjun Ma, Head of Deep Learning Technology Department at Baidu. “As an elastic deep learning framework for PaddlePaddle, we believe that EDL will substantially benefit the deployment of large-scale deep learning services, and the broader deep learning open source community.”

Baidu, also based in China, is the 8th largest Internet company in the world, topping $10 billion annually.

The LF Deep Learning Foundation, a Linux Foundation project, “accelerates and sustains the growth of artificial intelligence, machine learning and deep learning open source projects. The initiative’s Acumos AI Project is a platform and open source framework that makes it easy to build, share and deploy AI models. Backed by many of the world’s largest technology leaders, LF Deep Learning is a neutral space for harmonization and ecosystem engagement to advance AI, DL and ML innovation.

Organizations interested in contributing projects and learning more about LF Deep Learning Foundation, can go to www.deeplearningfoundation.org.




Edited by Ken Briodagh
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