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Christina Harter

Thank you ONNX & Amazon for Hosting a Great LF AI Day!

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A big thank you to Amazon and ONNX for hosting a great virtual meetup! The LF AI Day ONNX Community Virtual Meetup was held on October 14, 2020 and was a great success with over 100 attendees joining live. 

The meetup included ONNX Community updates, partner/end-user stories, and SIG/WG updates. The virtual meetup was an opportunity to connect with and hear from people working with ONNX across a variety of groups. A special thank you to Sheng Zha from Amazon for working closely with the ONNX Technical Steering Committee, SIGs, and ONNX community to curate the content.

Missed the meetup? Check out all of the presentations and recordings here.

This meetup took on a virtual format but we look forward to connecting again at another event in person soon. LF AI Day is a regional, one-day event hosted and organized by local members with support from LF AI, its members, and projects. If you are interested in hosting an LF AI Day please email info@lfai.foundation to discuss.

ONNX, an LF AI Foundation Graduated Project, is an open format to represent deep learning models. With ONNX, AI developers can more easily move models between state-of-the-art tools and choose the combination that is best for them.  Be sure to join the ONNX-Announce mailing list to join the community and stay connected on the latest updates. You can join technical discussions on GitHub and more conversations with the community on LF AI Slack’s ONNX channels.

ONNX Key Links

LF AI Resources

Thank you for Joining the LF AI Foundation at ONES 2020!

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Thank you to everyone who joined us last week at Open Networking & Edge Summit 2020! 

The event was held virtually this year, with over 1,300 people from 71 countries attending

The virtual LF AI Foundation booth was a hit! We had over 60 people visit our booth in the Gold & Bronze Hall and interact with our LF AI community members who were staffing the booth. Visitors were also able to download resources to learn more about each of LF AI’s projects, and they were able to give us insight into what type of projects they want to see in the future through our attendee survey. We were also able to engage with attendees in several great discussions, both at the booth and in the official ONES 2020 Slack workspace.

The session “The Making of 5G with AI & Open Source, presented by LF AI community member Mazin Gilbert, Vice President of Technology & Innovation at AT&T, was well attended! Attendees were able to hear how the marriage of 5G with edge cloud will enable next generation experiences like holograms for gatherings and meetings, mobile and untethered xR experiences for gaming and remote surgery, and immersive experiences for digital shopping.

Miss the session? If you registered for ONES, you can always view all of the session recordings on demand on the virtual event platform anytime. Or check back on the ONES website for a link to all of the sessions recordings on YouTube soon.

The LF AI Foundation mission is to build and support an open AI community, and drive open source innovation in the AI, ML, and DL domains by enabling collaboration and the creation of new opportunities for all the members of the community.

Want to get involved with the LF AI Foundation? Be sure to subscribe to our mailing lists to join the community and stay connected on the latest updates. 

LF AI Resources

Sparklyr 1.4.0 Release Now Available!

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Sparklyr, an LF AI Foundation Incubation Project, has released version 1.4.0! Sparklyr is an R Language package that lets you analyze data in Apache Spark, the well-known engine for big data processing, while using familiar tools in R. The R Language is widely used by data scientists and statisticians around the world and is known for its advanced features in statistical computing and graphics. 

In version 1.4.0, sparklyr adds a variety of improvements. Highlights include:

  • This release features efficient and parallelizable weighted sampling methods for Spark data frames. The technique being utilized by those methods is known as “exponential variates” (see https://blogs.rstudio.com/ai/posts/2020-07-29-parallelized-sampling)
  • Tidyr verbs such as `pivot_wider`, `pivot_longer`, `nest`, `unnest`, `separate`, `unite`, and `fill` now have specialized implementations in `sparklyr` for working with Spark data frames
  • Support for newly introduced higher-order functions in Spark 3.0 (e.g., `array_sort`, `map_filter`, `map_zip_with`, and many others)
  • Dplyr-related improvements:
    • All higher-order functions and sampling methods are made directly accessible through `dplyr` verbs
    • Made `grepl` part of the `dplyr` interface for Spark data frames
    • Thanks to a pull request from @wkdavis, `dplyr::inner_join`, `dplyr::left_join`, `dplyr::right_join`, and  `dplyr::full_join` now correctly replace `’.’` with `’_’` in the `suffix` parameter when working with Spark data frames (see https://github.com/sparklyr/sparklyr/issues/2648)
  • Support for newly introduced functionalities in Spark 3.0
    • Thanks to a pull request from @zero323, the `RobustScaler` functionality in Spark 3.0 is now supported in sparklyr through `ft_robust_scaler`
    • RAPIDS GPU acceleration plugin can now be enabled with `spark_connect(…, package = “rapids”)` and configured with `spark_config` options prefixed with “spark.rapids.”

The power of open source projects is the aggregate contributions originating from different community members and organizations that collectively help drive the advancement of the projects and their roadmaps. The sparklyr community is a great example of this process and was instrumental in producing this release. The sparklyr team wanted to give a special THANK YOU to the following community members for their contributions via pull requests (listed in chronological order):

To learn more about the sparklyr 1.4.0 release, check out the full release notes. Want to get involved with sparklyr? Be sure to join the sparklyr-Announce and sparklyr Technical-Discuss mailing lists to join the community and stay connected on the latest updates.

Congratulations to the sparklyr team and we look forward to continued growth and success as part of the LF AI Foundation! To learn about hosting an open source project with us, visit the LF AI Foundation website.

sparklyr Key Links

LF AI Resources

LF AI Day ONNX Community Virtual Meetup – Fall 2020

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Amazon, ONNX, and the LF AI Foundation are pleased to sponsor the upcoming LF AI Day* – ONNX Community Virtual Meetup – Fall 2020, to be held via Zoom on October 14th.

ONNX, an LF AI Foundation Graduated Project, is an open format to represent deep learning models. With ONNX, AI developers can more easily move models between state-of-the-art tools and choose the combination that is best for them. 

The virtual meetup will cover ONNX Community updates, partner/end-user stories, and SIG/WG updates. Check back on the event website for the agenda. If you are using ONNX in your services and applications, building software or hardware that supports ONNX, or contributing to ONNX, you should attend! This is a great opportunity to connect with and hear from people working with ONNX across many companies. 

Registration is now open and the event is free to attend. Capacity will be 500 attendees. For up to date information on this virtual meetup, please visit the event website

Want to get involved with ONNX? Be sure to join the ONNX-Announce mailing list to join the community and stay connected on the latest updates. You can join technical discussions on GitHub and more conversations with the community on LF AI Slack’s ONNX channels.

Note: In order to ensure the safety of our event participants and staff due to the Novel Coronavirus situation (COVID-19) the ONNX Steering Committee decided to make this a virtual-only event via Zoom.*LF AI Day is a regional, one-day event hosted and organized by local members with support from LF AI and its Projects. Learn more about the LF AI Foundation here.

ONNX Key Links

LF AI Resources

NNStreamer 1.6.0 Release Now Available!

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NNStreamer, an LF AI Foundation Incubation-Stage Project, has released version 1.6.0. NNStreamer is a set of Gstreamer plugins that support ease and efficiency for Gstreamer developers adopting neural network models and neural network developers managing neural network pipelines and their filters.

In version 1.6.0, NNStreamer adds a variety of improvements; highlights include:

  • New hardware accelerators and neural network frameworks support added: Verisilicon-Vivante, Qualcomm-SNPE, NNFW-ONE-Runtime, and Tensorflow2-lite.
  • Data serialization support with flatbuf and protobuf.
  • Android APIs optimized (i.e., invoke latency in Galaxy S20: 2ms → 0.1ms)
  • Plug-and-play sub-plugins support for tensor-converters
  • Hardware acceleration configuration reworked: multiple candidates may be expressed and options may be altered in run-time.
  • Fixes, semantics updates, and minor features added after commercialization (Galaxy Watch 3 and a few “next-year” products and Tizen 6 releases).

The NNStreamer Project invites you to adopt or upgrade to version 1.6.0 in your application, and welcomes feedback. To learn more about the NNStreamer 1.6.0 release, check out the change log and full release notes. Want to get involved with NNStreamer? Be sure to join the  NNStreamer-Announce and NNStreamer-Technical-Discuss mail lists to join the community and stay connected on the latest updates.

Congratulations to the NNStreamer team! We look forward to continued growth and success as part of the LF AI Foundation. To learn about hosting an open source project with us, visit the LF AI Foundation website.

NNStreamer Key Links

LF AI Resources

3 Trusted AI Toolkits Join LF AI as Newest Incubation Projects

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LF AI Foundation (LF AI), the organization building an ecosystem to sustain open source innovation in artificial intelligence (AI), machine learning (ML), and deep learning (DL), today is announcing 3 Trusted AI Toolkits as its latest Incubation Projects: AI Fairness 360 Toolkit, Adversarial Robustness Toolbox, and AI Explainability 360 Toolkit. All 3 toolkits were originally released and open sourced by IBM

AI Fairness 360 Toolkit

The AI Fairness 360 (AIF360) Toolkit is an open source toolkit that can help detect and mitigate unwanted bias in machine learning models and datasets. With the toolkit, developers and data scientists can easily check and mitigate for biases at multiple points along their machine learning lifecycle, using the appropriate fairness metrics for their circumstances. It provides metrics to test for biases, and algorithms to mitigate bias in datasets and models. The AI Fairness 360 interactive experience provides a gentle introduction to the concepts and capabilities. Recently, AIF360 also announced compatibility with Scikit Learn, and an interface for R users.

Adversarial Robustness 360 Toolbox

The Adversarial Robustness 360 (ART) Toolbox is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to evaluate, defend and verify Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, scikit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio, video, etc.) and machine learning tasks (classification, object detection, generation, certification, etc.).

AI Explainability 360 Toolkit

The AI Explainability 360 (AIX360) Toolkit is a comprehensive open source toolkit of diverse algorithms, code, guides, tutorials, and demos that support the interpretability and explainability of machine learning models. The AI Explainability 360 interactive experience provides a gentle introduction to the concepts and capabilities by walking through an example use case for different consumer personas.

See IBM’s full announcement on the donation here. Since IBM’s donation, we are pleased to announce that the Trusted AI projects have been approved by the LF AI TAC and have now been formally moved into the LF AI Foundation, complete with all the legal formalities, new logos, websites and GitHub locations.

Dr. Ibrahim Haddad, Executive Director of LF AI, said: “We are very pleased to welcome these Trusted AI open source projects to LF AI. For the past year, the Trusted AI Committee at LF AI has been actively working on building its community and defining a set of principles that AI software is expected to honor. With the addition of these three tools, our efforts now have a venue to codify these principles and provide an opportunity to collaborate on the code with the global community under a vendor-neutral and open governance. We look forward to supporting these projects and helping them to thrive and grow their community of adopters and contributors.” 

LF AI supports projects via a wide range of benefits; and the first step is joining as an Incubation Project. LF AI will support the neutral open governance for these Trusted AI projects to help foster the growth of the projects. 

“At IBM, at our core, we believe in the fair and equitable use of technology and this is especially true of artificial intelligence. Developers must ensure applications are built with trust and transparency,” said Todd Moore, Vice President, Open Technology, IBM, “Our AI Fairness toolkits and Watson OpenScale are enabling developers and data scientists to address bias, and explain the behavior of our models. By open sourcing IBM’s Adversarial Robustness 360, AI Fairness 360, and AI Explainability 360 toolkits through The LF AI Foundation, we all can advance the technology, in an open governance community and encourage the best and brightest to collaborate on one of the most pressing issues in this technological area.”

Trusted AI Video Series

To learn more about the Trusted AI projects, take a look at the 7-episode video series on YouTube, created by Anessa Petteruti (Computer Science senior at Brown University) in collaboration with LF AI:

EPISODE 1: Introducing Trusting AI: Unlocking the Black Box with Animesh Singh 

Artificial intelligence unlocks countless possibilities for the human race. But is there a darker side to the technology? In the opening episode of Trusting AI: Unlocking the Black Box, Animesh Singh, Chief Architect of the Artificial Intelligence and Machine Learning OSS Platform at IBM, introduces IBM and the Linux Foundation’s Trusted AI efforts.

EPISODE 2: Trusted AI Research with Aleksandra Mojsilović

Learn specifically about research conducted for Trusted AI in this interview with the Foundations of Trusted AI Lead, Aleksandra Mojsilović. Dr. Mojsilović, an IBM Fellow, also co-directs IBM’s Science for Social Good.

EPISODE 3: AI Explainability and Factsheets with Michael Hind

Michael Hind, Distinguished Research Staff Member at IBM Research AI, discusses one of Trusted AI’s toolboxes, AI Explainability 360, as well as AI Factsheets 360 in depth.

EPISODE 4: Ethical AI in Higher Education with Michael Littman

Universities all over the world have taken efforts to incorporate ethical teachings into artificial intelligence and machine learning courses. In Providence, Rhode Island, Professor Michael Littman of Brown University discusses AI ethics in higher education and the computer science department’s Responsible CS program.  

EPISODE 5: Adversarial Robustness with Mathieu Sinn

Artificial intelligence presents numerous benefits as well as security vulnerabilities. Mathieu Sinn, Senior Technical Staff Member and Manager of AI Security and Privacy at IBM, delves into Trusted AI’s Adversarial Robustness Toolbox and the program’s efforts to combat cyber attacks in AI.

EPISODE 6: Open Source and the Linux Foundation with Ibrahim Haddad

Ibrahim Haddad, Vice President of Strategic Programs at the Linux Foundation and Executive Director of LF AI, discusses the importance of open source in software development, specifically artificial intelligence.

EPISODE 7: Trusted AI in Production and MLOps with Tommy Li and Andrew Butler

How can developers use Trusted AI in their own projects? Find out from IBM software engineers Tommy Li and Andrew Butler who guide you through MLOps and using Trusted AI in production.

Get Involved

Check out the Trusted AI GitHub for Getting Started guides to start working with these projects today. Learn more about the Trusted AI toolkits on their websites (AI Fairness 360, AI Explainability 360, Adversarial Robustness Toolbox) and be sure to join the Trusted-AI-360-Announce and Trusted-AI-360-Technical-Discuss mail lists to join the community and stay connected on the latest updates. 

A warm welcome to these Trusted AI projects! We look forward to the projects’ continued growth and success as part of the LF AI Foundation. To learn about how to host an open source project with us, visit the LF AI website.

Trusted AI Key Links

LF AI Resources

Join the LF AI Foundation at OSS+ELC Europe 2020

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The LF AI Foundation is excited to announce our participation at the upcoming Open Source Summit + Embedded Linux Conference Europe 2020! The event will be held virtually, and registration is only $50 for four days of learning and collaboration. 

Below are all the different ways to interact with the LF AI Foundation at the conference. We hope to see you there!

Attend Sessions in the AI/ML/DL Track 

The LF AI Foundation will be hosting an AI/ML/DL Track at OSS EU. Join these sessions to learn the latest updates from our projects and hear from leaders in the AI industry. Register for OSS EU to attend.

Chat with us in the Virtual Exhibit Hall!

Come chat with us in the virtual exhibit hall at OSS EU. Various LF AI community members will be around all week to answer any questions you have. You’ll also be able to get more information on how to get involved with the LF AI Foundation.

Attend the LF AI Mini Summit!

We invite you to join us for our LF AI Foundation Mini Summit where we will cover the latest updates from the Foundation, Technical Advisory Council, Trusted AI Committee, and more. Also hear the latest updates from our ONNX, Amundsen, Angel and Marquez projects. We look forward to uncovering new collaboration opportunities among our growing community. 

Join us by registering to attend the Open Source Summit EU – Register Now

The LF AI Mini Summit is co-located with the Open Source Summit EU and will be held virtually on Thursday, October 29 at 14:00 – 15:30 Greenwich Mean Time Zone (GMT). You will need to be registered for OSS EU to attend. OSS EU registration costs $50 USD, which includes access to the LF AI Mini Summit.

The LF AI Foundation mission is to build and support an open AI community, and drive open source innovation in the AI, ML, and DL domains by enabling collaboration and the creation of new opportunities for all the members of the community. 

Want to get involved with the LF AI Foundation? Be sure to subscribe to our mailing lists to join the community and stay connected on the latest updates. 

LF AI Resources

LF AI Foundation Announces Graduation of Horovod Project

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The LF AI Foundation, the organization building an ecosystem to sustain open source innovation in artificial intelligence (AI), machine learning (ML) and deep learning (DL), is announcing today that hosted project Horovod is advancing from an Incubation level project to a Graduate level. This graduation is the result of Horovod demonstrating thriving adoption, an ongoing flow of contributions from multiple organizations, and both documented and structured open governance processes. Horovod has also achieved a Core Infrastructure Initiative Best Practices Badge, and demonstrated a strong commitment to community.

As an Incubation Project, Horovod utilized the LF AI Foundation’s various enablement services to foster its growth and adoption; including program management support, event coordination, legal services, and marketing services ranging from website creation to project promotion. 

Horovod is a distributed training framework for TensorFlow, Keras and PyTorch, which improves speed, scale and resource allocation in machine learning training activities. It was open sourced by Uber, the project founder, and joined LF AI as an Incubation Project in December 2018. 

“The journey of Horovod from Incubation to Graduation has been very impressive,” said Dr. Ibrahim Haddad, Executive Director of the LF AI Foundation. “The speed of development, the growth of its community, and its wide adoption is particularly noteworthy.  Horovod has exceeded all of our graduation criteria and we’re proud to be its host Foundation and to support them across a number of services. As a Graduate project, our support to Horovod will continue to increase as needed. This graduation is our way to present Horovod as an advanced and mature open source technology ready for large scale deployments. Congratulations, Horovod!”

Uber uses Horovod for self-driving vehicles, fraud detection, and trip forecasting. It is also being used by Alibaba, Amazon and NVIDIA. Contributors to the project outside Uber include Amazon, IBM, Intel and NVIDIA. 

“Since joining the LFAI, Horovod has developed into the industry-standard for training deep neural networks at scale, in every framework and on every platform,” said Travis Addair, Technical Lead for the Horovod project. “It’s a continued honor to collaborate with and learn from Horovod’s many exceptional contributors from across the deep learning community. This graduation is a major milestone for the Horovod project, and an acknowledgement of all the hard work and collaboration our contributors have put forward to make this project a success. As a graduated project, I am looking forward to broadening the reach of our community even further, working towards the goal of making deep learning training simple and intuitive to scale.”

Feature Roadmap for 2020

  • Elastic Training / Fault Tolerance
  • Horovod on Ray + Ray Tune Integration
  • Ludwig + Horovod Spark Estimator integration
  • TensorFlow / General Horovod Spark Estimator
  • MXNet Horovod Spark Estimator (Amazon)
  • Horovod Plugin Architecture (NVIDIA)
  • Horovod Spark Dynamic GPU Allocation (NVIDIA)

Curious about how Horovod can make your model training faster and more scalable? Try out the framework now. And be sure to join the Horovod Announce and Horovod Technical-Discuss mailing lists to join the community and stay connected on the latest updates. 

Congratulations to the Horovod team and we look forward to continued growth and success as part of the LF AI Foundation! To learn about hosting an open source project with us, visit the LF AI Foundation website.

Horovod Key Links

LF AI Resources

IBM Upgrades to Premier Membership

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The LF AI Foundation is pleased to announce that IBM has upgraded its membership from General to Premier, granting it a seat on the LF AI governing board and a voting representative on every LF AI committee. IBM now joins other leading technology companies such as AT&T, Baidu, Ericsson, Huawei, Nokia, Tech Mahindra, Tencent, Zilliz and ZTE as a Premier Member, enabling and supporting a sustainable open source AI ecosystem. 

Premier membership is the LF AI’s highest tier of membership, reserved for organizations who contribute heavily to the open source artificial intelligence (AI), machine learning (ML), and deep learning (DL) space. These organizations, along with members at the General and Associate levels, work in concert with LF AI team members, to take the most active role in enabling open source AI, ML and DL, growing the ecosystem, facilitating collaboration and integration efforts across projects, and spearheading efforts in areas such as interoperability, ethical and responsible AI. Learn more about joining LF AI here.

IBM has been actively involved in the LF AI Foundation since its inception, participating in its various committees and recently contributing three projects for incubation. We’re thrilled to see IBM’s continued commitment to the LF AI mission, and we look forward to partnering in this new capacity to help support open source innovation and projects within the AI, ML and DL space.

“The LF AI Foundation has created an environment that is truly advancing trustworthy artificial intelligence within the open source community,” said Todd Moore, IBM Vice President, Open Technology, “Increasing IBM’s support level to now be a Premier Member of the LF AI Foundation will aid the community and advance the future of AI.”

LF AI’s Growing Portfolio

The LF AI Foundation now has 17 hosted projects, with over 50 companies, 20 universities and 1,150 active developers contributing to these projects. In addition to our growing project portfolio, we’ve also seen significant increased participation in two key initiatives: The LF Workflow & Interop Committee and the Trusted AI Committee.

The ML Workflow & Interop Committee is focused on defining a standardized ML Workflow implemented with open source projects and tools, and promoting cross project integration and interoperability. The Trusted AI Committee is focused on creating policies, guidelines, tooling, and use cases by industry in this very important space. Both of these committees are open for participation and we welcome anyone interested to join the conversations by subscribing to the mail lists or attending an upcoming meeting; check out their wiki pages for more information. 

LF AI Membership

The LF AI Foundation now has 24 members who have hit the ground running in their engagement across the Premier, General, and Associate membership levels. We’ve seen a diverse group of companies getting involved across various industries and we welcome those interested in contributing to the support of open source projects within the AL, ML and DL space. You can think of LF AI as a greenhouse growing and sustaining open source AI, ML, and DL projects from seed to fruition. Interested in becoming a member of LF AI? Learn more membership opportunities here or email membership@lfai.foundation.

The LF AI Foundation’s mission is to build and support an open AI community, and drive open source innovation in the AI, ML and DL domains by enabling collaboration and the creation of new opportunities for all the members of the community.

LF AI Resources

Join the LF AI Foundation at ONES 2020

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The LF AI Foundation is excited to announce our participation at the upcoming Open Networking & Edge Summit 2020! The event will be held virtually on September 28 – 30, and registration is only US$50.

Below are all the different ways to interact with the LF AI Foundation at the conference. We hope to see you there!

Visit us at the LF AI Virtual Booth

Come chat with us at our virtual booth at ONES! Various LF AI community members will be available to answer any questions you have. You’ll also be able to get more information on how to get involved with the LF AI Foundation.

Attend our Session: The Making of 5G with AI & Open Source

We invite you to join LF AI Foundation Executive Director, Ibrahim Haddad, along with Mazin Gilbert, Vice President of Technology & Innovation at AT&T, for their session, “The Making of 5G with AI & Open Source”. 

The session will be on Monday, September 28 at 2:00 – 2:30pm Eastern Daylight Time (UTC -4). You will need to be registered for ONES in order to attend the session. More details on the session are below.

Over the next decade, we will be transformed by new revolutionary experiences that will radically change the way we work, live and play. The marriage of 5G with edge cloud will enable holograms for gatherings and meetings, mobile and untethered xR experiences for gaming and remote surgery, and immersive experiences for digital shopping. These experiences can only be brought to life through an intelligent 5G network that employs AI and open interfaces to enable zero-touch network automation, and elasticity to optimize traffic flow and spectrum. In this talk, Mazin will present the making of 5G with AI and Open Source as foundational elements to enable these next generation experiences and network automation. The role of ORAN-SC, ONAP, Akraino and Acumos-AI will be discussed.

Join us by registering to attend Open Networking & Edge Summit – Register Now

The LF AI Foundation mission is to build and support an open AI community, and drive open source innovation in the AI, ML, and DL domains by enabling collaboration and the creation of new opportunities for all the members of the community. 

Want to get involved with the LF AI Foundation? Be sure to subscribe to our mailing lists to join the community and stay connected on the latest updates. 

LF AI Resources