Mikael Ronström joins Logical Clocks as Head of Data. Mikael Ronström is the inventor and lead developer of NDB Cluster, an open-source distributed database underlying the MySQL Cluster platform.
Logical Clocks, the data company behind the world’s first Enterprise Feature Store for Machine Learning, today announced full support for Microsoft Azure on its cloud managed data platform, Hopsworks. The announcement complements the existing support for Amazon Web Service (AWS), thus enterprises can now manage features for training and serving models at scale on Hopsworks while maintaining control of their data inside their organisation’s accounts on the most popular cloud platforms.
Logical Clocks introduces a new machine learning technique to train models for fraud detection using deep learning and Generative Adversarial Networks (GANs). The technique, available on Hopsworks, the world’s first data platform with a Feature Store, helped Swedbank, the oldest and largest bank in Sweden, reduce costs associated with fighting fraud.
Logical Clocks announced it is developing the first enterprise Feature Store for Edge Computing for the AI-NET ANIARA project, part of the CELTIC-NEXT programme, to bring artificial intelligence to 5G networks in Europe. To meet infrastructural requirements on performance, security, reliability and scalability, the project will take advantage of Logical Clocks’ Feature Store.
Logical Clocks, the enterprise behind Hopsworks - the first data platform for designing and operating machine learning and artificial intelligence (AI) applications at scale with a Feature Store - announces the launch of Hopsworks.ai, the world’s first managed cloud platform for AI with a feature store.
On September 5th, 2019, Logical Clocks won the European DatSci award for “Data Science Technology Innovation of the Year”. Hopsworks is a data-intensive platform for data science and AI, that includes the first Enterprise Feature Store for Machine Learning.
Hopsworks 0.10 brings the latest features, improvements and bug fixes. It is the biggest release done so far, made up of 191 JIRAs including many new features. Also, this version marks the last of the 0.x series, as Hopsworks is gearing up towards its 1.x series starting with 1.0 end of Q3 2019.
Hopsworks 0.9.0 brings the latest features, improvements and bug fixes. It introduces Apache Airflow as-a-service which means users can now create their own workflows from within their familiar environment of a Hopsworks project. You can get started with Airflow in Hopsworks by visiting the user-guide.
Announcing the release of the first Enterprise Feature Store for Machine Learning. The Feature Store solves the problem of ad-hoc and siloed machine learning pipelines, where features, the training data for such pipelines, tend to become disorganized, disjointed, and duplicated, leading to correctness problems and redundant work.
Hopsworks 0.8.0 brings the latest features, improvements and bug fixes. It comes a short while after version 0.7.0 and brings the world’s first open-source feature store, a revamped REST API for managing jobs in Hopsworks and improvements in visualization for python notebooks.