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LF AI & Data

LF AI & Data is a foundation under the Linux Foundation dedicated to advancing open-source artificial intelligence (AI), machine learning (ML), and data projects. It fosters collaboration between industry leaders, researchers, and developers to create scalable, trustworthy, and interoperable AI and data solutions.

71 projects

79,900 contributors

$2B

vLLM

The mission of the Project is to develop an open-source library for fast LLM inference and serving.

Contributors

15,627

Organizations

1,267

Software value

$17M

ONNX

ONNX is an open format built to represent machine learning models. ONNX defines a common set of operators - the building blocks of machine learning and deep learning models - and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers.

Contributors

8,181

Organizations

948

Software value

$49M

DeepSpeed

The mission of the Project is to develop a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Contributors

5,376

Organizations

181

Software value

$20M

Milvus

As an open source vector similarity search engine, Milvus is easy-to-use, highly reliable, scalable, robust, and blazing fast. Adopted by over 100 organizations and institutions worldwide, Milvus empowers applications in a variety of fields, including image processing, computer vision, natural language processing, voice recognition, recommender systems, drug discovery, etc.

Contributors

4,603

Organizations

400

Software value

$38M

Delta Lake Project

Delta Lake is an open source storage layer that brings reliability to data lakes.

Contributors

3,720

Organizations

499

Software value

$39M

DELTA

Delta is a deep learning based end-to-end natural language and speech processing platform. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3.

Contributors

2,923

Organizations

38

Software value

$2M

DeepRec

The mission of the Project is to develop a high-performance recommendation deep learning framework.

Contributors

2,731

Organizations

224

Software value

$160M

FATE Project

FATE is an open-source project initiated by Webank’s AI Department to provide a secure computing framework to support the federated AI ecosystem.

Contributors

2,520

Organizations

110

Software value

$103M

Horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

Contributors

2,291

Organizations

328

Software value

$2.8M

CLAIMED

CLAIMED (Component Library for AI, Machine Learning, ETL and Data Science) is a runtime and programming language agnostic Data & AI component framework abstracting away all complexity for advanced MLOps and TrustedAI.

Contributors

2,069

Organizations

20

Software value

$3.6M

Kserve

The mission of the Project is to develop a highly scalable and standards based model inference platform on Kubernetes for Trusted AI.

Contributors

1,976

Organizations

370

Software value

$75M

Flyte

Flyte is a container-native, type-safe workflow and pipelines platform optimized for large scale processing and machine learning written in Golang.

Contributors

1,876

Organizations

322

Software value

$78M

Feast

Feast is the bridge between your data and your machine learning models allowing teams to register, ingest, serve, and monitor features in production.

Contributors

1,732

Organizations

335

Software value

$12M

Kedro Project

The mission of the Project is to design and implement an open source framework for creating reproducible, maintainable and modular data science code.

Contributors

1,728

Organizations

191

Software value

$50M

TonY Project

The mission of the Project is to design and implement an open source framework to run distributed deep learning jobs reliably on computing infrastructures.

Contributors

1,605

Organizations

36

Software value

$1M

Docling

Docling simplifies document processing, parsing diverse formats — including advanced PDF understanding — and providing seamless integrations with the gen AI ecosystem.

Contributors

1,562

Organizations

169

Software value

$692M

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.

Contributors

1,492

Organizations

217

Software value

$35M

Angel

A Flexible and Powerful Parameter Server for large-scale machine learning.

Contributors

1,487

Organizations

56

Software value

$23M

Pyro

Deep universal probabilistic programming with Python and PyTorch.

Contributors

1,397

Organizations

236

Software value

$24M

sparklyr

R interface for Apache Spark.

Contributors

1,310

Organizations

130

Software value

$2.1M

Ludwig

Ludwig is an open-source, declarative machine learning framework that makes it easy to define deep learning pipelines with a simple and flexible data-driven configuration system. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks.

Contributors

1,283

Organizations

152

Software value

$14M

Amundsen

Amundsen is a data discovery and metadata engine for improving the productivity of data analysts, data scientists and engineers when interacting with data. Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.

Contributors

1,086

Organizations

249

Software value

$8.8M

IREE

IREE (Intermediate Representation Execution Environment1) is an MLIR-based end-to-end compiler and runtime that lowers Machine Learning (ML) models to a unified IR that scales up to meet the needs of the datacenter and down to satisfy the constraints and special considerations of mobile and edge deployments.

Contributors

1,011

Organizations

107

Software value

$24M

Marquez

Marquez is an open source metadata service for the collection, aggregation, and visualization of a data ecosystem’s metadata. It maintains the provenance of how datasets are consumed and produced, provides global visibility into job runtime and frequency of dataset access, centralization of dataset lifecycle management, and much more. Marquez was released and open sourced by WeWork.

Contributors

825

Organizations

57

Software value

$3M

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.

Contributors

722

Organizations

57

Software value

$7.2M

OPEA

The mission of the Project is to develop an ecosystem orchestration framework to efficiently integrate performant GenAI technologies and workflows leading to quicker GenAI adoption and business value.

Contributors

643

Organizations

50

Software value

$61M

OpenFL

The mission of the OpenFL projet is to build a flexible, secure, scalable and easily learnable Federated Learning tool for data scientists and data owners.

Contributors

598

Organizations

40

Software value

$2.5M

Open Lineage

The mission of the Project is to enable the industry at-large to collect lineage metadata consistently and comprehensively across complex pipelines, creating a deeper understanding of data.

Contributors

597

Organizations

80

Software value

$11M

Recommenders

The mission of the Project is to develop examples and best practices for building recommendation systems, provided as Jupyter notebooks.

Contributors

588

Organizations

112

Software value

$3M

Egeria

Egeria provides the Apache 2.0 licensed open metadata and governance type system, frameworks, APIs, event payloads and interchange protocols to enable tools, engines and platforms to exchange metadata in order to get the best value from data whilst ensuring it is properly governed.

Contributors

578

Organizations

52

Software value

$68M

RWKV

The mission of the Project is to develop a recurrent neural net language model with GPT-level LLM performance, which can also be directly trained like a GPT transformer.

Contributors

564

Organizations

34

Software value

$47M

Elyra

The mission of the Project is to create and maintain an open-source development workspace that simplifies the creation and orchestration of the AI model development lifecycle tasks.

Contributors

493

Organizations

91

Software value

$23M

Monocle

The mission of the Project is to develop a domain specific tracing framework for monitoring code used to build Generative AI applications.

Contributors

469

Organizations

9

Software value

$684K

Neural Network (NN) Streamer

? Neural Network (NN) Streamer, Stream Processing Paradigm for Neural Network Apps/Devices.

Contributors

442

Organizations

42

Software value

$21M

AI Fairness 360

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

Contributors

391

Organizations

44

Software value

$2.8M

FlagAI

The mission of the Project is to develop a fast, easy-to-use and extensible toolkit for large-scale AI modeling, with the goal of supporting training, fine-tuning, and deployment of large-scale models on various downstream tasks with multi-modality.

Contributors

333

Organizations

27

Software value

$38M

DocArray

The mission of the DocArray project is to develop a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh.

Contributors

331

Organizations

47

Software value

$1.7M

Bee-AI

The mission of BeeAI is building an open-source ecosystem that empowers developers to discover, run, and compose AI agents from any framework. We’re creating the infrastructure to make agents truly interoperable, regardless of their underlying implementation.

Contributors

322

Organizations

33

Software value

$6.7M

LF AI & Data

LF AI & Data is an umbrella foundation of the Linux Foundation that supports open source innovation in artificial intelligence (AI) and data. LF AI & Data was created to support open source AI and data, and to create a sustainable open source AI ecosystem that makes it easy to create AI and data products and services using open source technologies. We foster collaboration under a neutral environment with an open governance in support of the harmonization and acceleration of open source technical projects.

Contributors

218

Organizations

37

Kompute

The mission of the Project is to advance the GPU Acceleration ecosystem in scientific and industry applications through cross-vendor graphics card tooling, and further capabilities for GPGPU computing across advanced data processing use-cases.

Contributors

201

Organizations

27

Software value

$580K

Data Prep Kit

Data Prep Kit accelerates unstructured data preparation for LLM app developers. Developers can use Data Prep Kit to cleanse, transform, and enrich use case-specific unstructured data to pre-train LLMs, fine-tune LLMs, instruct-tune LLMs, or build Retrieval Augmented Generation (RAG) applications for LLMs

Contributors

191

Organizations

10

Software value

$13M

Feathr

The mission of the Project is to develop an enterprise-grade, high performance feature store.

Contributors

179

Organizations

29

Software value

$6.2M

Substra

The mission of the Project is to design and implement an open source framework for traceable ML orchestration on decentralized sensitive data.

Contributors

179

Organizations

19

Software value

$5.6M

Xtreme1

The mission of the Project is to build an accessible open-source data-centric MLOps infrastructure to connect people, models and data.

Contributors

176

Organizations

22

Software value

$8.3M

AI Explainability 360

interpretability and explainability of data and machine learning models. 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.

Contributors

146

Organizations

18

Software value

$2.4M

Datashim

The mission of the Project is to design and implement an Open Source framework that provides seamless access to Data in Kubernetes environments.

Contributors

146

Organizations

46

Software value

$714K

Open Voice Network Interoperability Initiative

The Open Voice Network Interoperability Initiative is developing The “Message Envelope,” a universal, open API for voice/chatbot and language model interoperability, analogous to HTTP AND HTML.

Contributors

132

Organizations

35

Software value

$3.1M

Adlik

Adlik offers a end-to-end optimizing framework for deep learning models whose goal is to accelerate deep learning inference process both on cloud and embedded environments.

Contributors

112

Organizations

8

Software value

$2.6M

LakeSoul

The mission of the Project is to develop an end-to-end, realtime and cloud native Lakehouse framework with fast data ingestion, concurrent update and incremental data analytics on cloud storages for both BI and AI applications.

Contributors

72

Organizations

6

Software value

$5.6M

Data Practices

DataPractices.org was pioneered by data.world as a “Manifesto for Data Practices” of four values and 12 principles that illustrate the most effective, ethical, and modern approach to data teamwork. As a member of the foundation, datapractices.org will expand to offer open courseware and establish a collaborative approach to defining and refining data best practices.

Contributors

68

Organizations

7

Software value

$1.7M

Bitol

Within the BITOL project, the primary objective is to tackle multiple challenges, such as data normalization, ensuring the relevance of documentation, establishing service-level expectations, simplifying data and tool integration, and promoting a data product-oriented approach. These efforts offer several advantages, including stimulating innovation and streamlining integration processes. BITOL is a sandbox-stage project of the LF AI & Data Foundation. Contributed by: AIDA User Group in September 2023

Contributors

65

Organizations

18

Software value

$747K

Machine Learning eXchange (MLX)

The mission of the Project is to design and implement an open source Data and AI Assets Catalog and Execution Engine that allows the uploading, registration, execution, and deployment of AI pipelines and pipeline components, models, datasets and notebooks.

Contributors

64

Organizations

8

Software value

$370K

Elastic Deep Learning (EDL)

Elastic Deep Learning using PaddlePaddle and Kubernetes.

Contributors

61

Organizations

10

Software value

$692K

SapientML

The mission of the Project is to help data scientists rapidly create and amend AI models.

Contributors

59

Organizations

7

Software value

$1.5M

OpenDS4All

OpenDS4All is a project created to accelerate the creation of data science curricula at academic institutions. While a great deal of online material is available for data science, including online courses, we recognize that the best way for many students to learn (and for many institutions to deliver) content is through a combination of lectures, recitation or flipped classroom activities, and hands-on assignments.

Contributors

54

Organizations

12

Software value

$8.5M

Open Model Initiative

The mission of the Project is to support open community development of openly licensed baseline AI models for image, video and audio generation that individuals and organizations can use and augment in their own solutions.

Contributors

40

Organizations

7

Software value

$810K

RosaeNLG Project

An open source natural generation library.

Contributors

39

Organizations

10

Software value

$89M

SOAJS

SOAJS provides a complete enterprise open source microservice management platform.

Contributors

34

Organizations

9

Software value

$37M

1chipML

The mission of the 1chipML open source project is to design and implement a library for basic numerical crunching and machine learning for microcontrollers offering a highly reliable open framework to use on limited and low-power hardware.

Contributors

30

Organizations

7

Software value

$2M

OpenDataology

The mission of the OpenDataology project is to provide a crowd-sourced platform that provides approaches to analyze and document the license compliance risks of publicly available datasets used for Artificial Intelligence (AI) software. In addition, the project endeavors to develop and promote open standards that capture the metadata required for performing license compliance analysis, dataset license compliance analysis processes and supporting tools.

Contributors

27

Organizations

5

Software value

$508K