Telecommunication giant AT&T partners with H2O.ai to launch their co-built artificial intelligence-powered feature store. The feature store aims to manage and reuse machine learning data.
Both the companies have been working for the past few months to launch the industry’s first artificial intelligence feature store. It is a unique platform that has been built using cutting-edge technology and can be easily integrated with most of the machine learning pipelines.
The store is available by the name “H2O AI Feature Store.” The store automatically sends recommendations regarding feature updates to improve the performance of artificial intelligence models.
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Chief data officer at AT&T, Andy Markus, said, “With our expertise in managing and analyzing huge data flows, combined with H2O.ai’s deep AI expertise, we understand what business customers are looking for in this space and our Feature Store offering meets this need.”
He further added that feature stores are currently one of the most popular areas in artificial intelligence development. Feature stores help data scientists and engineers develop highly accurate features and deploy them quickly.
Earlier scientists have to spend a lot of time in feature engineering, but with H2O AI Feature Store, they can build high-end features and deploy them in production effortlessly. The feature store solves the most challenging problem of building and serving machine learning data to production, which makes it an integral component of the infrastructure stack for ML.
According to H2O.ai, the feature store comes with three main components –
- Offline store of features for training and batch scoring
- Online store for real-time scoring and streaming
- Metadata registry to enable search and collaboration
The feature store comes with out-of-the-box support for Snowflake, Teradata, Databrick, and many other related platforms.
Interested individuals can visit the official website of the H2O AI Feature Store and sign up to get early access.
