- The AI-NET ANIARA project is an initiative from a consortium of 23 organisations from Sweden, Germany, United Kingdom, Finland, and Turkey
- The project will take advantage of Logical Clocks’ Feature Store to meet infrastructural requirements on performance, security, reliability, and scalability
Logical Clocks has announced that it is developing the first enterprise Feature Store for Edge Computing for the AI-NET ANIARA project. It is a part of the CELTIC-NEXT program and aims to bring AI to 5G networks in Europe.
The AI-NET ANIARA project is an initiative from a consortium of 23 organisations from Sweden, Germany, the United Kingdom, Finland, and Turkey. It aims to bring together three technologies- 5G, edge-centric computing, and artificial intelligence to accelerate digital transformation in Europe across different sectors connected to 5G edge cloud technology.
€10 million fund from the EUREKA framework
Dr. Jim Dowling, CEO at Logical Clocks and associate professor at KTH Royal Institute of Technology in Sweden said, “‘Europe has a great position in 5G networks but it has fallen behind in the key areas of digital infrastructure – cloud, big data, and artificial intelligence. There is an increasing need for managed platforms that provide data services to forthcoming AI applications in the new Edge and 5G markets.”
This project is coordinated by Ericsson. It received a €10 million fund from the EUREKA framework to develop automation support for network edge infrastructure and applications. This will employ machine learning to complement or replace conventional manual and proprietary optimisation and prediction algorithms.
Logical Clocks’ Feature Store
The project will take advantage of Logical Clocks’ Feature Store to meet infrastructural requirements on performance, security, reliability, and scalability. Hopsworks Feature Store was launched in 2018 and it is an open-source feature store for machine learning.
Dowling adds, “A feature store is a central vault for documented, curated, and access-controlled features. The Hopsworks Feature Store will solve the problem of serving features at low latency to edge applications, reducing the cost of developing and deploying machine learning applications on 5G networks.”
