LF AI Delivers Acumos AI Clio Release
Third Acumos AI release adds and extends Model On Boarding, Design Studio, Federation, License Management
SAN FRANCISCO, Nov. 26, 2019 /PRNewswire/ -- The LF AI Foundation, the organization building an open AI community to drive open source innovation in artificial intelligence (AI), machine learning (ML) and deep learning (DL), today announced the third software release of the Acumos AI Project, codenamed Clio. Clio is focused on improving the experience with users for "first hand" feature requests like how to easily on board AI models, how to design and manage support for pluggable frameworks, how to more easily handle federation with ONAP and O-RAN, license management, and more.
Acumos AI is a platform and open source framework that makes it easy to build, share, and deploy AI apps. Acumos standardizes the infrastructure stack and components required to run an out-of-the-box general AI environment. This frees data scientists and model trainers to focus on their core competencies and accelerates innovation.
"Clio is an important step forward in the democratization of AI, making open source AI technology available and easily utilized and not limited to AI specialists and Data Scientists. The features introduced in this new Acumos release continue to pave the path towards AI accessibility, further extending users' ability to build and share AI applications more easily," said Dr. Ibrahim Haddad, Executive Director of the LF AI Foundation. "Clio marks a higher level of maturity; this is deployment grade. If you're considering Acumos AI, we invite you to experiment with it and experience the live instance of the marketplace available from https://marketplace.acumos.org,"
Major highlights of the Clio release include:
- ONAP Integration: Acumos AI/ML models can now be used in ONAP for virtualized network elements automation and optimization.
- ORAN 5G RIC/XApp Deployment: Acumos AI/ML models can be deployed in ORAN RIC as XApp micro services to help optimize virtualized RAN.
- IPR/Cross Company Licensing Entitlement: Companies can publish commercial models and negotiate license agreements for use of their models. Implementation of a new License Usage Manager feature enables the support of license entitlements for Acumos models.
- Data/Training Pipelines: New feature to help data scientists create, integrate and deploy NiFi data pipelines.
- Pluggable MLWB Framework: Enterprise Design Tools are now Integrated to support pluggable framework.
- Support for C/C++ Client: Acumos has added the ability to onboard and deploy ML models in C and C++ languages (in additional to Java, Python, and R).
- Onboarding Spark/Java: Acumos can now take advantage of the popular Apache Spark cluster computing framework when onboarding and deploying ML models.
- Model Ratings: Automated way of assigning initial ratings to models based on available metadata.
- Enhanced Platform Adaptation on Kubernetes: Through integration of a Jenkins server as a workflow engine, Acumos now supports customization to meet Operator needs in mission-critical business functions such as how Acumos ML solutions are assessed for compliance with license and security policies, and where/how Acumos ML solutions are deployed for use under Kubernetes.
"LF AI members, including Amdocs, ATT, Ericsson, Huawei, Nokia, Tech Mahindra, and others are contributing to the evolution of the platform to ease the onboarding and the deployment of AI models," said Dr. Ofer Hermoni, Chair of LF AI Technical Advisory Council. "Acumos was the first hosted project at the Graduate level with several ongoing efforts to integrate it with other LF AI projects. This highlights an increase in collaboration across hosted projects, serving our mission to reduce redundancies, and increase cross pollination and harmonization of efforts across projects."
Full release notes available here: https://wiki.acumos.org/display/REL/Acumos_Clio_Release
Supporting Quotes
"Since the days of Claude Shannon, AT&T has played an active role in the evolution of AI. And, Acumos is a shining example of how open collaboration and community engagement can excel this evolution faster than ever before," said Mazin Gilbert, Vice President of Advanced Technology and Systems at AT&T. "We're thrilled to work with industry leaders to make AI better, smarter and more accessible to everyone."
Sachin Desai, LF AI Board Member and Ericsson VP of Global AI Accelerator said, "Open Source contributions and collaborations are critical aspects of Ericsson's AI journey. We are excited to contribute to Acumos Clio release in areas such as licensing and integration with ONAP, related to its commercialization and industrialization to address the needs of our customers. We look forward to building on this in collaboration with our customers and Acumos ecosystem partners."
"Huawei congratulates the successful delivery of Acumos Clio release. The Acumos-ONAP Integration work will enable model-driven intelligence to enhance the network orchestration and automation. This deliverable can rapidly automate new services and support complete lifecycle management," said Bill Ren, Chief Open Source Liaison Officer, Huawei.
"Nokia welcomes the third release of Acumos, Clio. We find that the community has been very successful in continuing improving Acumos over the past releases, and the Clio release shows dedication of the Acumos community," said Jonne Soininen, Head of Open Source Initiatives, Nokia. "Nokia believes Acumos occupies a unique place in the industry, and this successful cooperation shows the power of working together on AI in open source."
"Orange is proud to contribute to the LF AI Acumos project as we are convinced that this Open Source Machine learning platform will cover some important future AI needs of telecom operators in the field of 5G and virtualized networks," said Emmanuel Lugagne Delpon, SVP Orange Labs Networks and Group CTO. "With Clio, a new step has been passed toward the full automated deployment of AI model in open source platform such as ONAP & ORAN and we are very impatient to use these new features in our Orange AI Marketplace."
"Tech Mahindra is excited to see Acumos reaching its third major milestone with the release of Clio. As part of our TechMNxt charter, co-innovation and co-creation in the field of AI & ML are one of our key focus areas, and we will continue to work towards the enhancement of Acumos platform," said Sachin Saraf, SVP and VBU Head, CME Business, Tech Mahindra. "Our enterprise grade solutions are playing a key role in accelerating the adoption of Linux Foundation Artificial Intelligence open source projects."
Acumos AI Key Statistics
- 8 Projects
- 62 Repositories
- 1.27M+ lines of code
- 4K+ Commits
- 84 Contributors
- 78 Reviewers
Acumos Resources
About LF AI Foundation
The LF AI Foundation, a Linux Foundation project, accelerates and sustains the growth of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) open source projects. Backed by many of the world's largest technology leaders, LF AI is a neutral space for harmonization and ecosystem engagement to advance AI, ML and DL innovation. To get involved with the LF AI Foundation, please visit https://lfai.foundation.
About The Linux Foundation
Founded in 2000, the Linux Foundation is supported by more than 1,000 members and is the world's leading home for collaboration on open source software, open standards, open data, and open hardware. Linux Foundation's projects are critical to the world's infrastructure including Linux, Kubernetes, Node.js, and more. The Linux Foundation's methodology focuses on leveraging best practices and addressing the needs of contributors, users and solution providers to create sustainable models for open collaboration. For more information, please visit us at linuxfoundation.org.
The Linux Foundation has registered trademarks and uses trademarks. For a list of trademarks of The Linux Foundation, please see our trademark usage page: https://www.linuxfoundation.org/trademark-usage. Linux is a registered trademark of Linus Torvalds.
Jesse Casman
reTHINKit Media
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+1.415.730.2793
SOURCE LF AI Foundation
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