LF AI & Data Foundation—the organization building an ecosystem to sustain open source innovation in artificial intelligence (AI), machine learning (ML), deep learning (DL), and Data open source projects—today is announcing FEAST as its latest Incubation Project. Feast (Feature Store) is an open source feature store for machine learning.
Today, teams running operational machine learning systems are faced with many technical and organizational challenges:
- Models don’t have a consistent view of feature data and are tightly coupled to data infrastructure.
- Deploying new features in production is difficult.
- Feature leakage decreases model accuracy.
- Features aren’t reused across projects.
- Operational teams can’t monitor the quality of data served to models.
Developed collaboratively between Gojek and Google Cloud in 2018, Feast was open sourced in early 2019. The project sets out to address these challenges as follows:
- Providing a single data access layer that decouples models from the infrastructure used to generate, store, and serve feature data.
- Decoupling the creation of features from the consumption of features through a centralized store, thereby allowing teams to ship features into production with minimal engineering support.
- Providing point-in-time correct retrieval of feature data for both model training and online serving.
- Encouraging reuse of features by allowing organizations to build a shared foundation of features.
- Providing data-centric operational monitoring that ensures operational teams can run production machine learning systems confidently at scale.
“Feast was created to address the data challenges we faced at Gojek while scaling machine learning for ride-hailing, food delivery, digital payments, fraud detection, and a myriad of other use cases” said Willem Pienaar, creator of Feast. “After open sourcing the project we’ve seen an explosion of demand for the software, leading to strong adoption and community growth. Entering the LF AI & Data Foundation is an important step for us toward decentralized governance and wider industry adoption and development.”
Jeremy Lewi, Kubeflow founder, said “Feast entering the LF AI & Data Foundation is both a major milestone for the project and recognition of the strides the project has made toward solving some of the hardest problems in productionizing data for machine learning. Technologies like Feast have the potential to shape the machine learning stack of the future, and with its incubation in LF AI & Data, the project now has the ideal environment to expand its community in building a best-in-class open source feature store.”
Dr. Ibrahim Haddad, Executive Director of LF AI & Data, said: “We are very excited to welcome FEAST to LF AI & Data and help it thrive in a vendor-neutral environment under an open governance model. With the addition of FEAST, we are increasing the number of hosted projects under the Data category and look forward to tighter collaboration between our data projects and all other projects to drive innovation in data, analytics, and AI open source technologies.”
LF AI & Data supports projects via a wide range of services, and the first step is joining as an Incubation Project. LF AI & Data will support the neutral open governance for FEAST to help foster the growth of the project. Check out the Documentation to start working with FEAST today. Learn more about FEAST on their GitHub and be sure to join the FEAST-Announce and FEAST-Technical-Discuss mail lists to join the community and stay connected on the latest updates.
A warm welcome to FEAST! We look forward to the project’s continued growth and success as part of the LF AI & Data Foundation. To learn about how to host an open source project with us, visit the LF AI & Data website.
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