Stockholm, February 10, 2021 - 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.
“The European Union leads the world when it comes to leveraging AI for the benefit of the environment and public health” comments Jim Dowling, CEO at Logical Clocks and Associate Professor at KTH Royal Institute of Technology in Sweden. “Research is part of our DNA and we are proud to be one of the few AI companies leading projects that will ultimately enhance quality of life, not just in the European Union, but around the world.”
The Human Exposome Assessment Platform (HEAP) is building a research platform, leveraging AI capabilities, to reveal the influence of environmental factors on human health, such as the link between airborne particles and predisposition to late-onset disease such as cancer. The project received €11 million funding from the European Union for 11 partners from 6 European countries to combine machine learning with computational statistics and develop powerful statistical modelling tools. With Hopsworks’ metadata mechanisms, which makes large volumes of data easily searchable, accessible and shareable, the HEAP platform will not only unlock new insights but it will also facilitate sharing data in a secure environment, becoming an open resource for the research communities as well as policy-makers across the world.
The DeepCube project tackles, through AI, urgent problems caused by climate change in Europe and the whole Mediterranean region, such as forecasting of localized extreme drought and deadly heat impacts in Africa. The project is part of a consortium formed by 9 organizations from 6 European countries that will combine cutting-edge technologies, such as the Hopsworks platform for machine learning, the Earth System Data Cube, and an advanced visualization tool, to extract meaningful information from a large volume of data and to develop data-driven AI models. Funded with €4 million million by the European Union, the project will develop AI applications by extracting extract data from the Copernicus Earth Observation programme which already produces annually more than 3 petabytes of free, open and high quality data from satellites and from non-conventional data sources, such as social network data, industry-specific data, and sensor data.
The ExtremeEarth project focuses on the most concerning issues of food security, such as water availability for irrigation of vegetation growth for the former. Currently 20 percent of the agricultural areas of the world are irrigated, producing 40 percent of the global food. The project is also dedicated to developing near real-time automated sea mapping, positively impacting the maritime sea navigation and safety, thus improving the life of 4 million people living in the Arctic. Currently, sea ice information is available either as ice charts or as satellite data, a practice that requires time consuming expert analysis to produce and, consequently, leads to less frequent updates than desired. With support of 11 organizations, the project is implementing state-of-the-art technologies such as Hopeworks Deep Learning and big data processing of massive amounts of data. ExtremeEarth received €6 million funding from the European Union and it is generating key insights for the development of sustainable practices with high significant financial impacts.
“The Hopsworks platform will play a major role in going beyond the current state of the state-of-the-art of AI technologies, especially when addressing large volumes of data and scale-out deep learning, while remaining open source. We will continue to make Hopsworks available for free to researchers across the world to bring answers to problems that concern all of us,” comments Dowling.
About Logical Clocks
Logical Clocks was founded by the team that created and continues to drive Hopsworks Feature Store, the world’s first and most complete feature store with an end-to-end machine learning platform. With offices in Stockholm, London and Palo Alto, Logical Clocks aims to simplify the process of refining data into intelligence at scale.
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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, 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.
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