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Welcome to the LF AI Foundation wiki, where you will find information with a cross project focus. For individual projects, follow the links below.




The LF AI Foundation is a project of The Linux Foundation that supports open source innovation in artificial intelligence, machine learning, and deep learning. The LF AI Foundation was created to support numerous technical projects within this important space.

With the LF AI Foundation, members are working to create a neutral space for harmonization and acceleration of separate technical projects focused on AI, ML, and DL technologies.

For more information, please view the How to Get Involved deck.

Questions? Please email info@lfai.foundation.

Current Projects

Title

Project

Status

Description

Acumos

Graduate

Acumos is an Open Source Platform, which supports design, integration and deployment of AI models. Furthermore, Acumos supports an AI marketplace that empowers data scientists to publish adaptive AI models, while shielding them from the need to custom develop fully integrated solutions.

GitHub: https://github.com/acumos

Adlik 



INCUBATION

Adlik is an end-to-end optimizing framework for deep learning models. The goal of Adlik is to accelerate deep learning inference process both on cloud and embedded environment.

GitHub: https://github.com/Adlik

Angel




Graduate

Angel is a high-performance distributed machine learning platform based on the philosophy of Parameter Server. It is tuned for performance with big data from Tencent and has a wide range of applicability and stability, demonstrating increasing advantage in handling higher dimension model.

GitHub: https://github.com/Angel-ML/angel

EDL

     

INCUBATION

EDL optimizes the global utilization of the cluster running deep learning job and the waiting time of job submitters. It includes two parts: a Kubernetes controller for the elastic scheduling of distributed deep learning jobs, and a fault-tolerable deep learning framework.

GitHub: https://github.com/PaddlePaddle/edl

ForestFlow


INCUBATION

ForestFlow is a scalable policy-based cloud-native machine learning model server. ForestFlow strives to strike a balance between the flexibility it offers data scientists and the adoption of standards while reducing friction between Data Science, Engineering and Operations teams.

GitHub: https://github.com/ForestFlow/ForestFlow

Horovod




INCUBATION

Horovod, a distributed training framework for TensorFlow, Keras and PyTorch, improves speed, scale and resource allocation in machine learning training activities. 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.

GitHub: https://github.com/horovod/horovod

Ludwig

INCUBATION

Ludwig is a toolbox that allows to train and test deep learning models without the need to write code.

GitHub: https://github.com/uber/ludwig

Marquez



INCUBATION

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.

GitHub: https://github.com/MarquezProject

Milvus



INCUBATION

Milvus is an open source similarity search engine for massive-scale feature vectors. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources. Milvus can be used in a wide variety of scenarios to boost AI development.

GitHub: https://github.com/milvus-io

NNStreamer


INCUBATION

NNStreamer (Neural Network Support as Gstreamer Plugins) 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.

GitHub: https://github.com/nnstreamer

ONNX



Graduate

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.

GitHub: https://github.com/onnx

Pyro


INCUBATION

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.

GitHub: https://github.com/pyro-ppl/pyro

sparklyr



INCUBATION

sparklyr is an R package that lets you analyze data in Spark while using familiar tools in R. sparklyr supports a complete backend for dplyr, a popular tool for working with data frame objects both in memory and out of memory. You can use dplyr to translate R code into Spark SQL.

GitHub: https://github.com/sparklyr/sparklyr


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