Hopsworks 3.4 is now generally available. This version adds support for multi-region high availability and integration with external Kafka clusters. With 3.4, we now allow users to customize the operating system libraries in their Python environment. We have also added new support for scheduling Python and Spark jobs (e.g., used to orchestrate machine learning pipelines).
In the upcoming quarter Hopsworks is supporting several prominent AI and Machine Learning conferences as a sponsor during. We are thrilled to be a part of these events and to actively participate as an exhibitor.
I ett betydande steg mot att främja AI-innovation i Norden har Hopsworks ingått ett partnerskap med AI Sweden för att erbjuda en testbädd till alla AI Swedens partners. Samarbetet syftar till att främja användningen av den senaste AI-tekniken bland nordiska företag och institutionella aktörer.
In a significant stride towards fostering AI innovation in the Nordics, Hopsworks has partnered with AI Sweden to provide a "testbed" environment to all of AI Sweden Partners. The collaboration aims to foster the adoption of cutting-edge AI technologies among Nordic businesses and institutional actors.
Hopsworks 3.3 is now generally available. This version includes two new APIs to retrieve data for batch inference (built using DuckDB and ArrowFlight server) and a REST API to retrieve data from the online feature store.
Hopsworks has partnered with OpenSearch, an open-source, vector database for building flexible, scalable, and future-proof AI applications. With this collaboration, OpenSearch is the vector database that powers Hopsworks feature store’s search capabilities for ML assets.
The Feature Store Summit returns for a third year in a row. The third edition of the summit will take place on October 11th and will be joined by several prominent companies in the Feature Store community. The CFP is open and still accepting contributions.
Hopsworks recently entered a partnership with MLOps platform Katonic. Katonic’s platform is used to develop, deploy, monitor, and manage advanced analytics and ML and AI solutions in a self-service, collaborative, governed, and secure manner.
Read about Hopsworks 3.1 and the new improvements in the feature store (time-series splits for training data, support for managing thousands of models), stability and user-interface.
Hopsworks 3.0 is a new release focused on best-in-class Python support, Feature Views unifying Offline and Online read APIs to the Feature Store, Great Expectations support, KServe and a Model serving
We go through the new features and developments in Hopsworks 2.5 that will benefit open-source users and customers alike.
Hopsworks has received an ISO 27001 certification, the globally recognized standard for establishing, implementing, maintaining, and continually improving an information security management system.
Hopsworks has successfully completed the AICPA Service Organization Control (SOC) 2 Type II audit.
In the spring of 2023 Hopsworks launched a new workshop series called “Models to production in two weeks - Introducing the Feature Store, MLOps, and FTI Pipelines“ led by CEO Jim Dowling.
With a tripling of growth in 2022, Hopsworks raised $6.5M in investment and brings in Lars Nordwall, former President and COO at the double unicorn Neo4j, as Executive Chair.
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.
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 0.9.0 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.
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.
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.
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.
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.
The company that launched Hopsworks, the world’s first open-source Feature Store for AI, raises a €5M Series A investment led by the Nordic VC Industrifonden with the participation of Inventure. Hopsworks has already attracted industry leading organizations including PaddyPower-Betfair, Getinge, and Swedbank.
Logical Clocks announces three new research projects part of the European Union (EU) Horizon 2020 research and innovation programme that will benefit from Hopsworks artificial intelligence (AI) capabilities to scale deep learning and enhance research focused on understanding environmental changes and improving healthcare in Europe. Hopsworks is the world’s first and most advanced managed Feature Store with an end-to-end AI platform for the development and operation of AI applications at scale.
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 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, 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.