Projects
The LF AI & Data Foundation supports open source projects within artificial intelligence and the data space.
1chipML
1chipML is an open source library for basic numerical crunching and machine learning for microcontrollers
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Acumos AI
Acumos AI is a platform and open source framework that makes it easy to build, share, and deploy AI apps.
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Adlik
Adlik is a toolkit for accelerating deep learning inference. The goal of Adlik is to accelerate deep learning inference process both on cloud and embedded environments.
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Adversarial Robustness Toolbox
Adversarial Robustness Toolbox (ART) provides tools that enable developers and researchers to evaluate, defend, certify and verify Machine Learning models and applications against the adversarial threats.
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AI Explainability 360
AI Explainability 360 is an open source toolkit that can help users better understand the ways that machine learning models predict labels using a wide variety of techniques throughout the AI application lifecycle.
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AI Fairness 360
AI Fairness 360 is an extensible open source toolkit that can help users understand and mitigate bias in machine learning models throughout the AI application lifecycle.
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Amundsen
Amundsen is a data discovery and metadata engine for improving the productivity of data analysts, data scientists and engineers when interacting with data.
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Angel ML
The Angel Project is a high-performance distributed machine learning platform based on Parameter Server, running on YARN and Apache Spark.
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BI & AI
The goal of this committee is to integrate the power of AI and BI to make it CI (Cognitive Intelligence) by combing the speed machines accelerate (AI) with the direction intuited by human insight (BI).
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DataOps Committee
The DataOps Committee in LF AI & Data is is a global group that consists of participants from various geographies focused on DataOps.
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DataPractices
DataPractices is a “Manifesto for Data Practices,” comprised of values and principles to illustrate the most effective, modern, and ethical approach to data teamwork.
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Datashim
Datashim is enabling and accelerating data access for Kubernetes/Openshift workloads in a transparent and declarative way.
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Delta
DELTA is a deep learning based end-to-end natural language and speech processing platform.
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Egeria
EDL is an Elastic Deep Learning framework designed to help deep learning cloud service providers to build cluster cloud services using deep learning frameworks such as PaddlePaddle and TensorFlow.
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Egeria Conformance
To ensure both consistency and alignment with the standards driven by Egeria, the Egeria Conformance program is available for vendors to showcase how they are shipping Egeria as part of their offering.
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Elastic Deep Learning
EDL is an Elastic Deep Learning framework designed to help deep learning cloud service providers to build cluster cloud services using deep learning frameworks such as PaddlePaddle and TensorFlow.
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Feast
Feast is an open source feature store for machine learning. It was developed as a collaboration between Gojek and Google in 2018.
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Flyte
Flyte is a production-grade, declarative, structured and highly scalable cloud-native workflow orchestration platform.
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ForestFlow
ForestFlow is a scalable policy-based cloud-native machine learning model server.
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Horovod
Horovod makes it easy to take a single-GPU TensorFlow program and successfully train it on many GPUs faster. Horovod also achieved significantly improved GPU resource usage figures.
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JanusGraph
JanusGraph is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster.
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Kedro
Kedro is an open-source Python framework for creating reproducible, maintainable and modular data science code.
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Kompute
Kompute is a general purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing use cases.
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KServe
KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks.
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Ludwig
Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.
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Machine Learning eXchange
Machine Learning eXchange (MLX) is a Data and AI Assets Catalog and Execution Engine. It allows upload, registration, execution, and deployment of: AI pipelines and pipeline components, models, datasets, and notebooks.
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Marquez
Marquez is an open source metadata service for the collection, aggregation, and visualization of a data ecosystem’s metadata.
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Milvus
Milvus is an open-source vector database that is highly flexible, reliable, and blazing fast. It supports adding, deleting, updating, and near real-time search of vectors on a trillion-byte scale.
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NNStreamer
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.
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ONNX
ONNX 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. ONNX is developed and supported by a community of partners.
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OpenBytes
OpenBytes aims to facilitate wider sharing of, and collaboration with, data in the AI community through the promotion of data standards and formats and enabling contributions of data.
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OpenLineage
OpenLineage proposes an open standard and API for lineage collection that data processing engines can implement to publish at run time details of the data sources that it is reading, the types of processing it is performing and the destination of the results.
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Pyro
Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. Pyro enables flexible and expressive deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling.
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RosaeNLG
RosaeNLG is an open source project, template-based Natural Language Generation (NLG) automating the production of relatively repetitive texts based on structured input data and textual templates, run by a NLG engine.
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SOAJS
SOAJS is an open source microservices and API management platform, SOAJS eliminates the IT plumbing challenges, so you can deploy microservices significantly earlier and faster.
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Sparklyr
Sparklyr is an open-source and modern interface to scale data science and machine learning workflows using Apache Spark™, R, and a rich extension ecosystem.
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Substra
Substra is a framework offering distributed orchestration of machine learning tasks among partners while guaranteeing secure and trustless traceability of all operations.
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TonY
TonY is a framework to natively run deep learning jobs on Apache Hadoop. It currently supports TensorFlow, PyTorch, MXNet and Horovod.
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Trusted AI
The LF AI & Data Trusted AI Committee is a global group working on policies, guidelines, tools and use cases by industry to ensure the development of trustworthy AI systems and processes to develop them continue to improve over time.
Learn MoreAcumos AI
Acumos AI is a platform and open source framework that makes it easy to build, share, and deploy AI apps.
Learn MoreAdversarial Robustness Toolbox
Adversarial Robustness Toolbox (ART) provides tools that enable developers and researchers to evaluate, defend, certify and verify Machine Learning models and applications against the adversarial threats.
Learn MoreAngel ML
The Angel Project is a high-performance distributed machine learning platform based on Parameter Server, running on YARN and Apache Spark.
Learn MoreEgeria
EDL is an Elastic Deep Learning framework designed to help deep learning cloud service providers to build cluster cloud services using deep learning frameworks such as PaddlePaddle and TensorFlow.
Learn MoreFlyte
Flyte is a production-grade, declarative, structured and highly scalable cloud-native workflow orchestration platform.
Learn MoreHorovod
Horovod makes it easy to take a single-GPU TensorFlow program and successfully train it on many GPUs faster. Horovod also achieved significantly improved GPU resource usage figures.
Learn MoreMilvus
Milvus is an open-source vector database that is highly flexible, reliable, and blazing fast. It supports adding, deleting, updating, and near real-time search of vectors on a trillion-byte scale.
Learn MoreONNX
ONNX 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. ONNX is developed and supported by a community of partners.
Learn MorePyro
Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. Pyro enables flexible and expressive deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling.
Learn MoreAdlik
Adlik is a toolkit for accelerating deep learning inference. The goal of Adlik is to accelerate deep learning inference process both on cloud and embedded environments.
Learn MoreAI Explainability 360
AI Explainability 360 is an open source toolkit that can help users better understand the ways that machine learning models predict labels using a wide variety of techniques throughout the AI application lifecycle.
Learn MoreAI Fairness 360
AI Fairness 360 is an extensible open source toolkit that can help users understand and mitigate bias in machine learning models throughout the AI application lifecycle.
Learn MoreAmundsen
Amundsen is a data discovery and metadata engine for improving the productivity of data analysts, data scientists and engineers when interacting with data.
Learn MoreDataPractices
DataPractices is a “Manifesto for Data Practices,” comprised of values and principles to illustrate the most effective, modern, and ethical approach to data teamwork.
Learn MoreDatashim
Datashim is enabling and accelerating data access for Kubernetes/Openshift workloads in a transparent and declarative way.
Learn MoreDelta
DELTA is a deep learning based end-to-end natural language and speech processing platform.
Learn MoreElastic Deep Learning
EDL is an Elastic Deep Learning framework designed to help deep learning cloud service providers to build cluster cloud services using deep learning frameworks such as PaddlePaddle and TensorFlow.
Learn MoreFeast
Feast is an open source feature store for machine learning. It was developed as a collaboration between Gojek and Google in 2018.
Learn MoreForestFlow
ForestFlow is a scalable policy-based cloud-native machine learning model server.
Learn MoreJanusGraph
JanusGraph is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster.
Learn MoreKedro
Kedro is an open-source Python framework for creating reproducible, maintainable and modular data science code.
Learn MoreKompute
Kompute is a general purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing use cases.
Learn MoreKServe
KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks.
Learn MoreLudwig
Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.
Learn MoreMarquez
Marquez is an open source metadata service for the collection, aggregation, and visualization of a data ecosystem’s metadata.
Learn MoreNNStreamer
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.
Learn MoreSOAJS
SOAJS is an open source microservices and API management platform, SOAJS eliminates the IT plumbing challenges, so you can deploy microservices significantly earlier and faster.
Learn MoreSparklyr
Sparklyr is an open-source and modern interface to scale data science and machine learning workflows using Apache Spark™, R, and a rich extension ecosystem.
Learn MoreSubstra
Substra is a framework offering distributed orchestration of machine learning tasks among partners while guaranteeing secure and trustless traceability of all operations.
Learn MoreTonY
TonY is a framework to natively run deep learning jobs on Apache Hadoop. It currently supports TensorFlow, PyTorch, MXNet and Horovod.
Learn More1chipML
1chipML is an open source library for basic numerical crunching and machine learning for microcontrollers
Learn MoreMachine Learning eXchange
Machine Learning eXchange (MLX) is a Data and AI Assets Catalog and Execution Engine. It allows upload, registration, execution, and deployment of: AI pipelines and pipeline components, models, datasets, and notebooks.
Learn MoreOpenBytes
OpenBytes aims to facilitate wider sharing of, and collaboration with, data in the AI community through the promotion of data standards and formats and enabling contributions of data.
Learn MoreOpenLineage
OpenLineage proposes an open standard and API for lineage collection that data processing engines can implement to publish at run time details of the data sources that it is reading, the types of processing it is performing and the destination of the results.
Learn MoreRosaeNLG
RosaeNLG is an open source project, template-based Natural Language Generation (NLG) automating the production of relatively repetitive texts based on structured input data and textual templates, run by a NLG engine.
Learn MoreBI & AI
The goal of this committee is to integrate the power of AI and BI to make it CI (Cognitive Intelligence) by combing the speed machines accelerate (AI) with the direction intuited by human insight (BI).
Learn MoreDataOps Committee
The DataOps Committee in LF AI & Data is is a global group that consists of participants from various geographies focused on DataOps.
Learn MoreTrusted AI
The LF AI & Data Trusted AI Committee is a global group working on policies, guidelines, tools and use cases by industry to ensure the development of trustworthy AI systems and processes to develop them continue to improve over time.
Learn More
